Body structure imaging

ABSTRACT

A method of medical image processing for images of body structures, comprising: receiving anatomical data to reconstruct an anatomical image of a region of a body of a patient, said region comprises a portion of at least one internal body part which borders or is spaced apart from a target tissue; receiving functional data from a functional imaging modality which images at least said portion of the region of the body of the patient; processing said anatomical image to generate at least one image mask corresponding to the zone outside of the wall of said at least one internal body part; correlating the at least one generated image mask with the functional data for guiding a reconstruction of a functional image depicting said target tissue; and providing the reconstructed functional image.

RELATED APPLICATIONS

This application claims priority from the following applications:

U.S. Provisional Patent Application No. 61/756,112 filed Jan. 24, 2013,U.S. Provisional Patent Application No. 61/776,599 filed Mar. 11, 2013,U.S. Provisional Patent Application No. 61/803,611 filed Mar. 20, 2013,U.S. Provisional Patent Application No. 61/831,664 filed Jun. 6, 2013,U.S. Provisional Patent Application No. 61/875,069 filed Sep. 8, 2013,U.S. Provisional Patent Application No. 61/875,070 filed Sep. 8, 2013,U.S. Provisional Patent Application No. 61/875,074 filed Sep. 8, 2013the contents of which are incorporated herein by reference in theirentirety.

This application is one of a set including the following PCTApplications:

“BODY STRUCTURE IMAGING” (Attorney Docket No. 58457); “BODY STRUCTUREIMAGING” (Attorney Docket No. 58459); “NERVE IMAGING AND TREATMENT”(Attorney Docket No. 58463); “BODY STRUCTURE IMAGING” (Attorney DocketNo. 58465);

all of which are cofiled on the same date as this application.

FIELD AND BACKGROUND OF THE INVENTION

The present invention, in some embodiments thereof, relates to methodsand systems of imaging and, more particularly, but not exclusively, tomethods and systems of medical localizing and monitoring as well as toimaging using a functional imaging modality, e.g., a single photonemission computed tomography (SPECT) and/or positron emission tomography(PET).

Volumetric scans such as CAT scans, positron emission tomography (PET)scans, computerized tomography (CT) scans, magnetic resonance imaging(MRI) scans, Ultrasound scans, laser three dimensional (3D) scanners,and the like are commonly used, particularly in the medical industry, toobserve objects within a structure that would otherwise be unobservable.These scans have greatly advanced the capability of professionals suchas physicians. Conventional volumetric scan is intended to produce avolumetric image of a large volume of the body at high resolution. Theability to perform a volumetric scan with high resolution requires alarge number of detectors, a fine motion control, and abundantprocessing resources for allowing the acquisition of a high resolutionvolumetric image in a reasonable time. Furthermore, when the volumetricscan images a relatively large area, such as the torso, the patientradiation dose is relatively high, for example when the volumetric scanis a CT scan.

Usually, volumetric imaging of a body structure is a multi-stageprocess. First biochemical, radioactive and/or contrast agents may beadministered. Then, measurements are taken at a set of predeterminedviews at predetermined locations, orientations, and durations. Then, thedata is analyzed to reconstruct a volumetric image of the body structureand an image of the body structure is formed. The imaging process issequential, and there is no assessment of the quality of thereconstructed image until after the measurement process is completed.Where a poor quality image is obtained, the measurements must berepeated, resulting in inconvenience to the patient and inefficiency inthe imaging process.

The volumetric scan is usually performed by orbiting detectors frommultiple directions in order to provide sufficient information toreconstruct a three-dimensional image of the radiation source by meansof computed tomography. The detectors are typically mounted on a gantryto provide structural support and to orbit the detector around theobject of interest. If the detector is a nuclear medicine detector, suchas scintillation detector or CZT detectors, for example single photonemission computed tomography (SPECT) and positron emission tomography(PET) systems detector, a collimator that is used to restrict radiationacceptance, or the direction of ray travel, is placed between thedetector and the object being imaged. Typically this collimator isconstructed to provide a multiplicity of small holes in a dense,high-atomic-number material such as lead or Tungsten. The rays will passthrough the holes if they travel in a direction aligned with the holebut will tend to be absorbed by the collimator material if they travelin a direction not aligned with the holes.

SUMMARY OF THE INVENTION

There is provided, in accordance with some embodiments of the presentinvention, methods and systems for locating objects of desired shape(e.g., tissue, nerves, cancer) based on a functional image obtained froma functional imaging modality of an intra-body volume of a patient.Optionally, the functional image is combined with an anatomical image,and the nerve tissue is located based on the combined images. Optionallythe object of desired shape is detected using a model of nearby tissue.

According to an aspect of some embodiments of the present inventionthere is provided a method of medical image processing for images ofbody structures, comprising: receiving anatomical data to reconstruct ananatomical image of a region of a body of a patient, said regioncomprises a portion of at least one internal body part which borders oris spaced apart from a target tissue; receiving functional data from afunctional imaging modality which images at least said portion of theregion of the body of the patient; processing said anatomical image togenerate at least one image mask corresponding to the zone outside ofthe wall of said at least one internal body part; correlating the atleast one generated image mask with the functional data for guiding areconstruction of a functional image depicting said target tissue; andproviding the reconstructed functional image.

Optionally, the target tissue is a nerve tissue.

Optionally, the anatomical data is obtained form an anatomical imagingmodality.

Optionally, the at least one image mask is generated based onpreselected anatomical considerations of the at least one internal bodypart that contain target nerve tissue that have intensity activityregistered within the functional data.

Optionally, the at least one image mask is generated based on templatesthat define the location of target nerve tissue within and/or inproximal to the at least one internal body part.

Optionally, the method further comprises adjusting the shape of theimage mask based on functional data readings from correspondinganatomical data that does not include target nerve tissue.

Optionally, the image masks are generated based on anatomical locationsof target nerve structures with different levels of functionalsensitivity to a radioagent.

Optionally, the method further comprises normalizing the functional databased on measurements denoting activity of the target nerve tissue.

Optionally, the method further comprises removing functional datadenoting noise from anatomical regions that do not contain target nervetissue based on the anatomical data of the regions that do not containtarget nerve tissue.

Optionally, the reconstructed functional image contains regions wherethe target nerve structures are located and/or precise coordinates ofthe target nerve structures.

Optionally, there are two image cutters, one for the wall of the bodystructure and another for the outside of the wall of the body structure,the two image cutters being different from each other.

Optionally, the method further comprises correlating target nerves withtissue types.

Optionally, the method further comprises identifying the target nervestructures based on at least one predefined rule.

Optionally, the at least one predefined rule comprises being larger thana 2D or 3D size.

Optionally, the at least one predefined rule comprises comparing a radiolabeled molecule activity level compared to an average value and/orstandard deviation of molecular activity level across at least one of:the organ volume, within the image mask.

Optionally, the radio labeled molecule is metaiodobenzylguanidine(mIBG).

Optionally, the method further comprises calculating at least oneparameter for the identified target nerve structures.

Optionally, the image mask is a mapping of a 3D volume or 2D area, forcorrelating a volume or an area of the anatomical image to thecorresponding functional image.

Optionally, the functional imaging modality is a single photon emissioncomputed tomography (SPECT) modality.

Optionally, the anatomical imaging modality is selected from the groupcomprising: computed tomography (CT), 3D ultrasound (US), 2D US,magnetic resonance imaging (MRI).

Optionally, the method further comprises applying the image mask to aregistration of the anatomical image and the functional image.

Optionally, the method further comprises segmenting the anatomical imageinto different regions to generate the image masks for detectingdifferent GPs within the segmented regions.

Optionally, the method further comprises generating the at least oneimage mask based on the segments.

Optionally, a plurality of different sets of image masks are generatedto correspond to different parts of the structure of the internal bodypart containing nerves.

Optionally, a plurality of image masks are generated to detect differentnerve structures of different types and/or at different locations.

Optionally, the method further comprises calculating functional activitywithin the at least one generated image mask correlated with thefunctional data, and normalizing the calculated functional activity.

Optionally, the method further comprises registering the reconstructedfunctional image with a navigation system for one or both of treatmentand diagnosis.

Optionally, the method further comprises generating a spatialconnectivity map of the identified nerve structures that illustrates therelative spatial relationship between nerve structures.

Optionally, the method further comprises combining nerve structuresidentified based on different image masks, into a single dataset of atleast some identified nerve structures.

Optionally, the anatomical image denotes structures of tissuesinnervated by nerves.

Optionally, the functional image denotes functional activity of thenerves innervating a tissue structure.

Optionally, the size and shape of the image masks are generated tocontain target nerves innervating a tissue structure.

Optionally, correlating further comprises positioning the at least oneimage mask to correspond with regions of the target nerve tissue withinthe functional image.

Optionally, the method is repeated for different time frames and asingle reconstructed image is generated.

Optionally, the anatomical images are obtained during a cyclicphysiological process, wherein different spatiotemporal image masks aregenerated for images obtained during different phases of thephysiological process, the different spatiotemporal image masks aresynchronized with the physiological process to correspond to the samelocation of the tissues.

Optionally, the anatomical images obtained during a cyclic physiologicalprocess are registered, morphed, and a single set of image masks aregenerated.

Optionally, the size of the image masks for a hollow organ are selectedbased on the thickness of the organ wall.

Optionally, the method is performed before an ablation treatment of thetissue, to identify the location of the tissue.

According to an aspect of some embodiments of the present inventionthere is provided a method of medical image processing for images ofnerve tissue of an ANS of a heart, comprising: receiving anatomicalimage data to reconstruct an anatomical image of heart structuresinnervated by the ANS; receiving a functional data from a functionalimaging modality which images at least the heart structures innervatedby the ANS; selecting at least one image mask by processing theanatomical image, the at least one image mask corresponding todimensions of heart chamber walls containing nerve tissues; applying theat least one selected image mask with the functional data for guiding areconstruction of a functional image depicting the GPs; and providingthe reconstructed functional image.

Optionally, the nerve tissues are GPs.

Optionally, the at least one image mask is oversized compared to theheart wall chamber.

Optionally, the at least one image mask is generated based onpreselected anatomical regions of the heart that contain target nervetissue that have intensity activity registered within the functionaldata.

Optionally, the at least one image mask is generated based on templatesthat define the location of GPs in proximity to heart chamber walls.

Optionally, the at least one image mask is generated based on templatesthat define the location of GPs within heart chamber walls.

Optionally, the at least one image mask is generated based on templatesthat define the location of GPs that are located more than about 2 mmfrom the heart chamber walls.

Optionally, the method further comprises adjusting the shape of theimage mask based on functional data readings from correspondinganatomical data of blood chambers and/or vessels that do not includeGPs.

Optionally, the method further comprises cancelling functional datadenoting noise from inside blood filled chambers and/or vessels of theheart based on the anatomical data.

Optionally, the functional imaging modality is SPECT and the anatomicalimaging modality is at least one of CT and MRI.

Optionally, the anatomical images are obtained during a cardiac cycle,wherein different spatiotemporal image masks are selected for at leastsome images obtained during the cardiac cycle, the differentspatiotemporal image masks are synchronized with the cardiac cycle tocorrespond to the same location of the heart.

Optionally, the anatomical image is an average image composed of the enddiastolic volume image and the end systolic volume image.

Optionally, the method further comprises segmenting the anatomical imageinto walls of the heart chambers.

Optionally, the method further comprises selecting the at least oneimage mask based on the heart chamber wall segments.

Optionally, a first set of image masks is selected to correspond to anepicardium and tissue outside the myocardium, and a second set of imagemasks is selected to correspond to the myocardium.

Optionally, the method further comprises calculating functional activitywithin correlated image masks, and normalizing the calculated activityto identify the GPs.

Optionally, the functional activity is calculated for all image maskswithin the volume of the heart.

Optionally, the method further comprises identifying GPs based on atleast one predefine rule comprising the GP being larger than apredefined size.

Optionally, the predefined sizes are different for epicardial GPslocated within an epicardium and myocardial GPs located within amyocardium.

Optionally, the method further comprises identifying GPs based on atleast one predefine rule comprising calculated activity above apredefined threshold.

Optionally, the predefined threshold is based on a predefined factortimes a calculated standard deviation of activity within the image maskabove a calculated average activity within the image mask, and thecalculated adjacent activity surrounding an active region is lower thanhalf of the activity of the active region.

Optionally, the method further comprises calculating at least oneparameter for identified GPs.

Optionally, the at least one parameter is selected from one or more of:average size, specific activity, power spectra, normalized power spectraand GP connectivity map, number of GPs per predefined area.

Optionally, the at least one parameter is calculated for at least oneimage of the cardiac cycle.

Optionally, the method further comprises identifying changes in the atleast one parameter over time.

Optionally, the method further comprises displaying the identified GPsat least one image of multiple frames of a cardiac cycle.

Optionally, the method further comprises registering the identified GPswith a navigation system for treatment.

According to an aspect of some embodiments of the present inventionthere is provided a method of medical image processing for images of oneor more ANS components, the method being carried out by at least onemodule programmed to carry out the steps of the method, which comprise:receiving anatomical data from an anatomical imaging modality toreconstruct an anatomical image of a region of a body of a patient, saidregion comprises a portion of at least one internal body part whichborders or comprises an ANS component; receiving functional data from afunctional imaging modality which imaged at least said portion of theregion of the body of the patient; processing said anatomical image togenerate at least one image mask having dimensions that correspond todimensions of said at least one internal body part; applying the atleast one generated image mask with the functional data forreconstruction of a functional image depicting said ANS component; andidentifying one or more ANS components in the functional image.

According to an aspect of some embodiments of the present inventionthere is provided a method of medical image processing for images of GPsof an ANS of a heart, the method being carried out by at least onemodule programmed to carry out the steps of the method, which comprise:receiving anatomical image data from an anatomical imaging modality toreconstruct an anatomical image of heart structures innervated by theANS; receiving a functional data from a functional imaging modalitywhich images at least the heart structures innervated by the ANS;generating at least one image mask by processing the anatomical image,the at least one image mask corresponding to dimensions of heart chamberwalls containing GPs; applying the at least one selected image mask withthe functional data for locating one or more GPs of an ANS of a heart.

According to an aspect of some embodiments of the present inventionthere is provided a method of guiding a cardiac treatment using afunctional imaging modality, comprising: providing functional imagingmodality data from a functional imaging modality which images anintrabody volume of a patient containing a heart, the patient havingbeen injected with an imaging agent having a nervous tissue uptake by anautonomic nervous system (ANS) of the heart, the ANS comprising at leastone GP; locating the at least one GP innervating the heart based on thefunctional imaging modality data; and providing the located at least oneGP.

Optionally, the ANS comprises at least one GP comprising one or more of:superior left GP (SLGP), inferior left GP (ILGP), anterior right GP(ARGP), inferior right GP (IRGP), and Marshall GP.

Optionally, the ANS comprises two, three or more GPs from two or threeor more of: superior left GP (SLGP), inferior left GP (ILGP), anteriorright GP (ARGP), inferior right GP (IRGP), and Marshall GP.

Optionally, the method further comprises setting up a system forablating the located at least one GP to treat cardiac disease based onimproper activity of the located at least one GP.

Optionally, the cardiac disease comprises atrial fibrillation.

Optionally, the coordinates of the located GPs are loaded into anintrabody navigation system for displaying the location of the GPsrelative to the treatment or other diagnosis EP catheter.

Optionally, the coordinates of the located GPs are loaded into a CARTO®system for displaying the location of the GPs relative to the treatmentcatheter of the CARTO® system.

Optionally, the method further comprises navigating a catheter withinthe patient based on the CARTO® system.

Optionally, the method further comprises functionally verifyingtreatment points for GP ablation based on the CARTO® system.

Optionally, the method further comprises ablating the located GPs withthe CARTO® system.

Optionally, the method further comprises confirming ablation of the GPswith the CARTO® system.

Optionally, locating comprises locating the at least one GP in a fat pador other surrounding tissue of the heart based on the functional imagingmodality data. Optionally, setting up the system comprises setting upthe system for ablating the at least one GP within the fat pad withoutablating most of the surrounding fat pad.

Optionally, the method further comprises acquiring anatomical imagingmodality data from an anatomical image modality which images anintrabody volume of the patient containing the heart, and whereinlocating comprises locating the at least one GP in the intrabody volumeor next to the intrabody volume of the heart based on registration ofthe functional imaging modality data and the anatomical imaging modalitydata.

Optionally, the method further comprises marking the located at leastone GP on the anatomical imaging modality data.

Optionally, the anatomical imaging modality data is acquired in realtime during a treatment procedure by fluoroscopy, the locating isperformed before and/or in real time during the treatment procedure byCT, and the location of the at least one GP is presented to an operatorperforming the treatment procedure.

Optionally, the method further comprises generating an ANS mapcomprising a distribution and/or activity of one or both of ANS synapsesand GPs, and providing the ANS map for display.

Optionally, the ANS map is overlaid on a reconstructed anatomical imageof the heart containing a treatment or imaging probe within the heart,within the same space as the reconstructed anatomical image and CARTO®mapping image.

Optionally, the locating comprises identifying an intersection between acomplex fractionated atrial electrogram (CFAE) site and a contractileforce (CF) site, the guiding comprises guiding the ablation of theintersection.

Optionally, the locating comprises identifying an intersection between acomplex fractionated atrial electrogram (CFAE) site and a dominantfrequency (DF) site, the guiding comprises guiding the ablation of theintersection.

Optionally, the locating comprises identifying an intersection between acomplex fractionated atrial electrogram (CFAE) site and at least one GP,the guiding comprises guiding the ablation of the intersection.

Optionally, the locating comprises identifying an intersection between acomplex fractionated atrial electrogram (CFAE) site, a dominantfrequency (DF) and at least one GP, the guiding comprises guiding theablation of the intersection.

Optionally, the locating comprises identifying an intersection between acomplex fractionated atrial electrogram (CFAE) site, a contractile force(CF) site and at least one GP, the guiding comprises guiding theablation of the intersection.

Optionally, the locating comprises imaging at least one GP and mappingaround the located GP to verify the position of the GP.

Optionally, the method further comprises selecting a patient based on ahypothesis that the patient is suffering from improper activity of theheart ANS.

Optionally, acquiring comprises acquiring to contain data multipleframes during at least one cardiac cycle and reconstructing a singleimage.

Optionally, the method further comprises monitoring the effects ofablation on the heart.

Optionally, the method further comprises confirming effects of ablationbased on a generated ANS model.

According to an aspect of some embodiments of the present inventionthere is provided a system for identifying ANS tissue within an image ofa heart of a patient, the system comprising: a module for receivingfunctional imaging modality data from a functional imaging modalitywhich images an intrabody volume of a patient containing a heart, thepatient having been injected with an imaging agent having a nervoustissue uptake by an autonomic nervous system (ANS) of the heart, the ANScomprising at least one GP; a module for receiving anatomical imagingmodality data from an anatomical imaging modality which images anintrabody volume of a patient containing the heart; a module forlocating the at least one GP innervating the heart based on thefunctional imaging modality data; and a module for positioning thelocated at least one GP on the anatomical imaging data.

Optionally, the ANS comprises at least one GP comprising one or more of:superior left GP (SLGP), inferior left GP (ILGP), anterior right GP(ARGP), inferior right GP (IRGP), and Marshall GP.

Optionally, the ANS comprises two, three or more GPs from two or threeor more of: superior left GP (SLGP), inferior left GP (ILGP), anteriorright GP (ARGP), inferior right GP (IRGP), and Marshall GP.

Optionally, the anatomical imaging modality data is received beforeand/or during a treatment procedure.

Optionally, the system further comprises a catheter cardiac navigationsystem, the catheter cardiac navigation system receiving and displayingthe located nervous tissue for guiding the intra-body treatment probewithin the heart to ablate the nervous tissue.

Optionally, the catheter cardiac navigation system is CARTO®.

Optionally, the catheter cardiac navigation system is a 3Delectrophysiological (EP) system.

Optionally, the system further comprises an intra-body treatment probefor ablation of the nervous tissue within the heart.

Optionally, the intra-body treatment probe is at least one of aradiofrequency (RF) treatment probe, a cryosurgery treatment probe, anda probe that injects a toxin or medication.

Optionally, the system further comprises a diagnosis module forcomparing the distribution of the imaged nervous tissue with one or moresets of expected distributions, and detecting abnormal synapticdistribution and/or activity based on the comparison.

Optionally, the system further comprises a tracking module for trackingchanges in the distribution of the imaged nervous tissue over time.

Optionally, the system further comprises a repository for storing atleast one of generated ANS models and diagnosis.

Optionally, the system further comprises a module for estimating theprediction of success of an ablation procedure based on measured uptakeof the functional image.

Optionally, the system further comprises a user input element forreceiving manual input from a user, and a treatment planning module forannotating the located nervous tissue based on the received manualinput.

Optionally, the system further comprises a function verification modulefor at least one of stimulating a nervous tissue in a certain intrabodyarea and identifying one or more nervous responses in response to thestimulation.

Optionally, the system further comprises a module for comparing effectsof stimulation of nervous tissue after treatment with effects ofstimulation of nervous tissue before treatment, based on a generated ANSmodel, to confirm the treatment.

Optionally, the modules of the system are distributed.

According to an aspect of some embodiments of the present inventionthere is provided a system for identifying ANS components within animage of a heart of a patient, the system comprising: at least onemodule for: receiving functional imaging modality data from a functionalimaging modality which images an intrabody volume of a patientcontaining a heart, the patient having been injected with an imagingagent having a nervous tissue uptake by an autonomic nervous system(ANS) of the heart, the ANS comprising at least one GP comprising one ormore of: superior left GP (SLGP), inferior left GP (ILGP), anteriorright GP (ARGP), inferior right GP (IRGP), and Marshall GP; receivinganatomical imaging modality data from an anatomical imaging modalitywhich images an intrabody volume of a patient containing the heart; andlocating the at least one GP in the intrabody volume of the heart basedon the functional imaging modality data and anatomical imaging modalitydata.

According to an aspect of some embodiments of the present inventionthere is provided a method of imaging nervous tissue, comprising:acquiring functional imaging modality data from a functional imagingmodality which images an intrabody volume of a patient having a bodypart, the patient having been injected with an imaging agent having anervous tissue uptake by an autonomic nervous system (ANS); and locatingthe nervous tissue in the intrabody volume based on the functionalimaging modality data.

Optionally, the method further comprises generating an image of the ANSbased on the located nervous tissue with activity levels.

Optionally, the image indicates activity levels of the located nervetissue.

Optionally, the method further comprises setting up a system fortreatment of the located nervous tissue to treat disease based onimproper activity of the located nervous tissue.

Optionally, the method further comprises acquiring anatomical imagingmodality data from an anatomical image modality which images anintrabody volume of the patient containing the body part, and whereinlocating comprises locating the nervous tissue in the intrabody volumeof the heart based on the functional imaging modality data and theanatomical imaging modality data.

Optionally, the method further comprises positioning the located nervoustissue on the anatomical imaging modality data.

Optionally, the anatomical imaging modality data is acquired in realtime during a treatment procedure, the locating is performed beforeand/or in real time during the treatment procedure, and the location ofthe nervous tissue is presented to an operator performing the treatmentprocedure.

Optionally, locating comprises locating at least one ganglionic plexus(GP) of the ANS, with a size of between 1 and 20 mm in maximal diameter.

Optionally, locating comprises locating at least two ganglionic plexus(GP) of the ANS, with a size of between 1 and 20 mm in maximal diameter.

Optionally, the method further comprises generating an ANS mapcomprising a distribution and/or activity of one or both of ANS synapsesand GPs, and providing the ANS map for display.

Optionally, the method further comprises overlaying the ANS map with animage representation of an organ containing the nervous tissue.

Optionally, the method further comprises diagnosing the patient, thediagnosing comprising estimating an effect of the ANS on an organ basedon one or both of activity and distribution of synapses and/or ganglionswith respect to the organ.

Optionally, the method further comprises stimulating the ANS inconjunction with an imaging thereof and distinguishing between afferentand efferent activity based on the stimulation and the imaging.

Optionally, the method further comprises estimating an effect or changein effect and/or response of an autonomous nervous system and/or anorgan based on one or both of activity and distribution of synapsesand/or ganglions with respect to the organ, before, during and/or afterthe treatment.

Optionally, the method further comprises assigning the functionalimaging modality data to spatial locations according to a model of astructure of an organ identifying the nervous tissue synapses and/orinnervations based on data associated with the organ.

Optionally, the method further comprises providing a mapping functionwhich maps for at least one region in the intrabody volume of areference kinetic behavior, and applying the mapping function on thefunctional data to locate the nervous tissue in the intrabody volume.

Optionally, the method further comprises stimulating a nervous tissue inan intrabody volume of a patient to trigger a nervous responseassociated with a reference uptake value, acquiring, during the nervousresponse, functional data from the functional modality which images theintrabody volume, and localizing the nervous tissue in the intrabodyvolume according to the reference uptake value.

Optionally, the method further comprises acquiring anatomical data froman anatomical imaging modality which images the intrabody volume of thepatient and localizing the target nervous tissue in the intrabody volumebased on both the functional data and the anatomical data.

Optionally, the method further comprises identifying at least one regionof interest (ROI) in an intrabody area according to a match with areference value representing a reference uptake rate of an organ.

Optionally, localizing comprises filtering at least part of arepresentation of the intrabody volume in the functional data based on amatch with a reference value.

Optionally, localizing comprises analyzing data from the functional datato identify at least one region of interest (ROI) in the intrabodyvolume, the analysis is based on a three dimensional (3D) model of theanatomy of the intrabody volume.

Optionally, localizing comprises identifying at least one anatomiclandmark based on an analysis of respective portions of the functionaldata to register with an anatomic image.

Optionally, localizing comprises identifying a predefined pattern of adynamic behavior of the imaging agent in at least a region of theintrabody area.

Optionally, the method further comprises targeting a sub region in theintrabody area as a target for a medical treatment.

Optionally, the functional data is captured before, during, after,and/or after a treatment given to the patient.

Optionally, the method further comprises acquiring a location of anintra-body treatment probe in the intrabody volume, and presenting boththe functional data and the probe location to an operator during medicalprocedure.

Optionally, the method further comprises guiding a catheterizationprocedure for ablation based on the functional data, wherein the guidingis performed according to a combination between the functional data andan anatomical data of the intrabody area.

Optionally, the method further comprises applying a force to position anablation element on a catheter and/or selecting a level of ablationenergy, based on the location of the nervous tissue in the intrabodyvolume.

Optionally, the nervous tissue is selected from a group consisting of acarotid body nervous tissue, an aortic arch nervous tissue, a pulmonarynervous tissue, a renal nervous tissue, a splenic nervous tissue, ahepatic nervous tissue, an inferior mesenteric nervous tissue, asuperior mesenteric nervous tissue, a muscular nervous tissue, astomach, and a penile nervous tissue.

Optionally, the anatomical imaging modality data is received beforeand/or during a treatment procedure.

According to an aspect of some embodiments of the present inventionthere is provided a system for identifying ANS components within animage of an intrabody volume of a patient, the system comprising: amodule for receiving functional imaging modality data from a functionalimaging modality which images an intrabody volume of a patient having abody part containing nervous tissue, the patient having been injectedwith an imaging agent having nervous tissue uptake by an autonomicnervous system (ANS); a module for acquiring anatomical imaging modalitydata from an anatomical image modality which images an intrabody volumeof the patient containing the body part; and a module for locating thenervous tissue in the intrabody volume based on the functional imagingmodality data.

Optionally, the system further comprises a module for positioning thelocated nervous tissue on the anatomical imaging modality data.

Optionally, the functional imaging modality is selected from a groupconsisting of an electrocardiogram-gated SPECT (GSPECT) modality, aSPECT-CT modality and D-SPECT modality, and/or A-SPECT.

Optionally, the system further comprises a module for receiving ananatomical image from an anatomical imaging modality which images anintrabody volume of the patient containing the nervous tissue, and amodule for combining the anatomical image with the functional image.

Optionally, the anatomical imaging modality is selected from a groupconsisting of a positron emission tomography (PET) modality, acomputerized tomography (CT) modality, a magnetic resonance imaging(MRI) modality, and an Ultrasound modality.

Optionally, the system further comprises a module for generating an ANSmap comprising a distribution and/or activity of one or both of ANSsynapses and GPs.

Optionally, the imaging agent is metaiodobenzylguanidine (mIBG).

Optionally, the nervous tissue is a neural fiber.

Optionally, the nervous tissue is composed of synapses.

Optionally, the nervous tissue is a part of a peripheral nervous tissue.

Optionally, the nervous tissue is part of at least one ofparasympathetic nervous tissue and sympathetic nervous tissue.

Optionally, the nervous tissue includes at least one ganglionic plexus(GP).

Optionally, the nervous tissue is selected from a group consisting of acarotid body nervous tissue, an aortic arch nervous tissue, a pulmonarynervous tissue, a renal nervous tissue, a splenic nervous tissue, ahepatic nervous tissue, an inferior mesenteric nervous tissue, asuperior mesenteric nervous tissue, a muscular nervous tissue, astomach, and a penile nervous tissue.

Optionally, the system further comprises an intra-body treatment probefor intraoperative ablation of the nervous tissue.

Optionally, the system further comprises a navigation system for theintra-body treatment probe, the navigation system adapted for displayingthe located nervous tissue.

Optionally, the system further comprises imaging apparatus programmed tocontrol one or more of injection, acquisition and/or reconstruction soas to identify one or both of ganglia and synapse density in innervatedtissue.

Optionally, the system further comprises an output element programmed todisplay a 2D or 3D or higher dimensional map of distribution of synapsesand/or ganglia with respect to a tissue volume or an organ, based on theimaging data.

Optionally, the system further comprises a module to estimate an effectof an autonomous nervous system on an organ.

Optionally, the system further comprises imaging apparatus programmed toselectively identify and/or measure and/or display one or more ofsympathetic nervous tissue, innervated tissue, afferent pathways,efferent pathways and parasympathetic tissue.

Optionally, 2-6 GPs are identified.

Optionally, the size of the identified GPs ranges from about 2×2×2 mm toabout 4×4×4 mm.

Optionally, the system further comprises a storage unit for storing areconstructed image of the identified nervous tissue.

Optionally, the system further comprises a module for displaying apersonalized GP map on an anatomical image.

Optionally, activity levels are displayed on the anatomical image.

According to an aspect of some embodiments of the present inventionthere is provided a system for identifying ANS components within animage of an intrabody volume of a patient, the system comprising: atleast one module for: receiving functional imaging modality data from afunctional imaging modality which images an intrabody volume of apatient having a body part containing nervous tissue, the patient havingbeen injected with an imaging agent having nervous tissue uptake by anautonomic nervous system (ANS); acquiring anatomical imaging modalitydata from an anatomical image modality which images an intrabody volumeof the patient containing the body part; and locating the nervous tissuein the intrabody volume based on the functional imaging modality dataand anatomical imaging modality data.

Unless otherwise defined, all technical and/or scientific terms usedherein have the same meaning as commonly understood by one of ordinaryskill in the art to which the invention pertains. Although methods andmaterials similar or equivalent to those described herein can be used inthe practice or testing of embodiments of the invention, exemplarymethods and/or materials are described below. In case of conflict, thepatent specification, including definitions, will control. In addition,the materials, methods, and examples are illustrative only and are notintended to be necessarily limiting.

Implementation of the method and/or system of embodiments of theinvention can involve performing or completing selected tasks manually,automatically, or a combination thereof. Moreover, according to actualinstrumentation and equipment of embodiments of the method and/or systemof the invention, several selected tasks could be implemented byhardware, by software or by firmware or by a combination thereof usingan operating system.

For example, hardware for performing selected tasks according toembodiments of the invention could be implemented as a chip or acircuit. As software, selected tasks according to embodiments of theinvention could be implemented as a plurality of software instructionsbeing executed by a computer using any suitable operating system. Insome exemplary embodiments of the invention, one or more tasks accordingto exemplary embodiments of method and/or system as described herein areperformed by a data processor, such as a computing platform forexecuting a plurality of instructions. Optionally, the data processorincludes a volatile memory for storing instructions and/or data and/or anon-volatile storage, for example, a magnetic hard-disk and/or removablemedia, for storing instructions and/or data. Optionally, a networkconnection is provided as well. A display and/or a user input devicesuch as a keyboard or mouse or touch screen are optionally provided aswell.

BRIEF DESCRIPTION OF THE DRAWINGS

Some embodiments of the invention are herein described, by way ofexample only, with reference to the accompanying drawings. With specificreference now to the drawings in detail, it is stressed that theparticulars shown are by way of example and for purposes of illustrativediscussion of embodiments of the invention. In this regard, thedescription taken with the drawings makes apparent to those skilled inthe art how embodiments of the invention may be practiced.

In the drawings:

FIG. 1 is a schematic diagram of an autonomic nervous system, to helpunderstand some embodiments of the present invention;

FIG. 2A is a flowchart of a method of localizing nervous tissue based ona combination of anatomical data and functional data of an intrabodyvolume, according to some embodiments of the present invention;

FIG. 2B is a flow chart of a computer-implemented method for combiningthe functional and anatomical images and/or locating the GPs, inaccordance with some embodiments of the present invention;

FIG. 3 is a schematic block diagram of a system for localizing nervoustissue based on a combination of anatomical data and functional data ofan intrabody volume, according to some embodiments of the presentinvention;

FIG. 4 is a flowchart of a clinical protocol wherein a patient isinjected with radio labeled metaiodobenzylguanidine, according to someembodiments of the present invention;

FIG. 5 is a schematic illustration of a human heart and a set of fourganglionic plexi and their axons;

FIG. 6 is a flowchart of a method for performing an ablation treatmentby mapping complex fractionated atrial electrograms, contractile forcesites, and/or dominant frequency sites in the atria as target areas foran treatment, such as ablation, according to some embodiments of thepresent invention;

FIGS. 7A-7D, 8A-8D, 9A-9D, 10A-10D and 11A-11D are sets of figures thatdepicts activity sites in the heart which are set as areas forablations, according to some embodiments of the present invention, whereeach set includes four views (clockwise): right anterior oblique (RAO).Posterior-anterior (PA) view, a right lateral view (left side) and aposterior view (right side);

FIG. 12 is a flowchart of a method of localizing a nervous tissue basedon an association of different regions in a SPECT image to differentorgans and/or tissues based on a mapping function, according to someembodiments of the present invention;

FIG. 13 shows an image of the left atrium and left ventricle, in whichthe left atrium is colored in accordance with a radio labeledmetaiodobenzylguanidine (mIBG) molecule activity according to exemplaryembodiments of the invention, showing a maximal activity level in theleft inferior pulmonary vein;

FIG. 14 shows an image of the right ventricle and left ventricle, inwhich the right ventricle is colored in accordance with mIBG activityaccording to exemplary embodiments of the invention, showing a maximalactivity level in the intra ventricular septum;

FIG. 15 shows an image of the left atrium colored in accordance withmIBG activity, according to exemplary embodiments of the invention;

FIGS. 16, 17, 18, 19, 20 show steps in treatment of GP sites, accordingto some embodiments of the present invention.

FIGS. 21A, 21B, and 21C show GP sites localized, according to exemplaryembodiments of the invention, where each one of these figures includes,from left to right, a transverse cut image, a coronal cut image, andsagittal cut image;

FIGS. 22A and 22B show the GP sites of FIGS. 21A, 21B, and 21C afterestimated locations have been correlated with a map of typicalanatomical GP locations in the heart;

FIG. 22C show the GP sites of FIGS. 21A, 21B, and 21C after estimatedlocations have been overlaid on sympathetic synapse density maps;

FIGS. 23A, 23B, 23C and 23D show GP sites localized, according to anexemplary embodiment of the invention, where each one of these figuresincludes, from left to right, a transverse cut image, a coronal cutimage, and sagittal cut image;

FIG. 24 shows the location of localized GP sites integrated into a Cartosystem for ablation guidance, according to some embodiments of theinvention;

FIG. 25 depicts HFS application site (marked with a circle having adashed pattern) on a 3D simulation of the heart of a patient andlocalized according to some embodiments of the present invention;

FIG. 26 depicts a negative response to the appliance of HFS in theapplication site depicted in FIG. 25;

FIGS. 27A and 27B depict HFS application site (marked with a circlehaving a dashed pattern) on a 3D simulation of the heart of a patientand localized according to some embodiments of the present invention;

FIG. 28 depicts a positive response to the appliance of HFS in theapplication site depicted in FIGS. 27A and 27B;

FIGS. 29 and 30 depict repeating the HFS application at the GP Sitedepicted in FIGS. 27A and 27B;

FIG. 31 depicts a positive response to the appliance of HFS in theapplication site depicted in FIGS. 29 and 30;

FIGS. 32 and 33 depict HFS application site (marked with a circle havinga dashed pattern) on a 3D simulation of the heart of a patient andlocalized according to some embodiments of the present invention;

FIG. 34 depicts a positive response to the appliance of HFS in theapplication site depicted in FIGS. 35 and 36;

FIGS. 35 and 36 depict ablation site (marked with a circle having adashed pattern) on a 3D simulation of the heart of a patient andlocalized according to some embodiments of the present invention;

FIGS. 37 and 38 depict negative HFS response in a post ablationmeasurement;

FIG. 39 depicts an ablation site (marked with a circle having a dashedpattern) on a 3D simulation of the heart of a patient and localizedaccording to some embodiments of the present invention;

FIGS. 40 and 41 depict a negative HFS response in a post ablationmeasurement;

FIGS. 42 and 43 depict an ablation site (marked with a circle having adashed pattern) on a 3D simulation of the heart of a patient andlocalized according to some embodiments of the present invention;

FIGS. 44A, 44B, 44C and 44D show GP sites localized, according to anexemplary embodiment of the invention, where each one of these figuresincludes, from left to right, a transverse cut image, a coronal cutimage, and sagittal cut image;

FIG. 45 shows the location of localized GP sites integrated into a Cartosystem for ablation guidance, according to some embodiments of theinvention;

FIGS. 46A, 46B, and 46C show GP sites localized, according to anexemplary embodiment of the invention, where each one of these figuresincludes, from left to right, a transverse cut image, a coronal cutimage, and sagittal cut image; and

FIG. 47 shows the location of localized GP sites integrated into a Cartosystem for ablation guidance, according to some embodiments of theinvention.

DESCRIPTION OF EMBODIMENTS OF THE INVENTION

The present invention, in some embodiments thereof, relates to methodsand systems of imaging and, more particularly, but not exclusively, tomethods and systems of medical localizing and/or monitoring and/orimaging and/or mapping using a functional imaging modality, for example,single photon emission computed tomography (SPECT).

As used herein, the phrase functional imaging modality means an imagingmodality that is designed to or otherwise configured to producefunctional based data and/or images (e.g., of an intrabody organ or apart thereof), for example, a nuclear based modality such assingle-photon emission computed tomography (SPECT), positron emissiontomography (PET), functional magnetic resonance imaging (fMRI), or othermodalities. The images may be based on changes within tissues, forexample, chemical composition (e.g., at nerve synapses), releasedchemicals (e.g., at synapses), metabolism, blood flow, absorption, orother changes. The images may provide physiological functional data, forexample, activity of nervous system tissue.

As used herein, the phrase anatomical imaging modality means an imagingmodality that is designed to produce structural based data and/or images(e.g., anatomical image), for example, X-rays, ultrasound (US), computedtomography (CT), such as x-ray or gamma-ray, magnetic resonance imaging(MRI), or other modalities. Organs, tissues and/or other structures maybe detected by the anatomical image.

The present invention, in some embodiments thereof, relates to the useof radiolabeled tracers (also referred to as radiotracer or radioagentor tracer) and/or radiopharmaceuticals, for example, ametaiodobenzylguanidine (mIBG) tracer or another imaging agent forimaging and/or localization (e.g., medical localizing) and/or monitoringand/or mapping (e.g., to obtain synapse distribution in an organ) of theautonomic nervous system (and more particularly for identifying nervoustissue, GP, or other structures) and diagnosis and/or treatment thereof.Optionally, the radiolabeled tracer is a nervous activity tissue marker,for example, denoting activity of neurotransmitters such asnorepinephrine (NE). As used herein, the terms marker, imaging agent,and radioactive tracer, and radiolabeled tracer are all interchangeable.Optionally, nerve tissues are detected, for example, the presence ofsignificant nerve tissues is detected (e.g., GPs innervating the organof interest) over non-significant nerve tissue (e.g., GPs innervatingother organs).

An aspect of some embodiments of the invention relates to diseases,medical conditions and/or disease conditions (may be usedinterchangeably herein) that may be caused, exacerbated or sustained, orotherwise affected by input or involvement of the autonomic nervoussystem (ANS). Examples of such disease conditions include hypertension,cardiac arrhythmias, diabetes and irritable bowel syndrome. In someembodiments of the invention, such disease conditions may be diagnosedand/or monitored. In some embodiments, such disease conditions may betreated by input or involvement of the autonomic nervous system, e.g.,GP ablation.

Some embodiments of the invention relate to means and/or methods for useof such means for detecting the connection between the autonomic nervoussystem and the organ affected by improper activation of the autonomicnervous system (e.g., innervated organ), for example, based on acombination of functional imaging data and optionally anatomical imagingdata.

Some embodiments of the invention relate to means and/or methods for useof such means for diagnosing the disturbance and/or improper activationof the ANS, for example, by comparing acquired functional imaging dataor information derived therefrom to a set of reference data (e.g.,reference images—for example: of the same patient or a healthy person).

Some embodiments of the invention relate to means and/or methods for useof such means for determining and/or guiding a therapy for the disease,for example, by providing reconstructed functional imaging data thatidentifies the location of nervous tissue for registration withanatomical images (e.g., to a treatment navigation system, such asCartoMerge™ module).

Also provided in accordance with some embodiments of the invention aremeans and/or methods for monitoring or guiding the therapy and/orfollowing up on the patients treated (e.g., every few days, weeks,months and/or years and/or according to progress of the disease and/orchange in treatment regimen). For example, following up may includemonitoring the nerve tissues e.g., locating and tracking over time todetect changes. Optionally, the therapy may be modified, e.g., stopped,continued, increased and/or changed, based on data obtained in thefollowing up.

An aspect of some embodiments of the invention relates to identifyingnervous tissue, for example cardiac related nervous tissue,gastrointestinal related nervous tissue, smooth muscle related nervoustissue, and/or nervous tissue associated with other organs and/ortissues. In some exemplary embodiments of the invention, the nervoustissue detected and/or identified includes synapses and/or nervoustissue which innervates a target tissue, such as the heart, bladder,eye, gastrointestinal organs (e.g., stomach, intestines), respiratoryrelated tissues, muscles, glands, liver, pancreas, adrenal, kidney,sexual organs, bladder, or other organs and/or tissues. Additionalexamples of innervated tissue are provided with reference to FIG. 1.

In some exemplary embodiments of the invention, the innervating tissueis automatically identified and/or otherwise visually presented and/ormeasured by injecting a marker selectively taken up by nervous tissue(e.g., mIBG). Optionally, anatomical segmentation is used to distinguishbetween innervating nervous tissue (e.g., to a target organ) andseparate nervous tissue (e.g., not to the target organ), and/or eitheror both from other tissues (non-nervous tissue e.g., fat, muscle,connective tissue, glands). Optionally, both types of nervous tissue areshown. Optionally or alternatively, structural and/or functionallimitations on the separate nervous tissue, such as size, locationand/or shape are used to distinguish between innervating nervous tissue,separate nervous tissue, and other tissues. In some exemplaryembodiments of the invention, the relative amount of innervation and/oractivity of innervating nervous tissue may be determined by calculatinga relative amount of activity in different parts of said tissue, withrespect to the injected radioisotope—e.g., nervous activity tissuemarker.

In some exemplary embodiments of the invention, an image may bedisplayed showing both functional and structural details of an organ(e.g., heart) and of the nervous system (e.g., nerves innervating theorgan). In some exemplary embodiments of the invention, functionaldetails of the nervous system include both synapses and ganglions.Optionally or alternatively, functional details of the heart includemetabolism (e.g., based on uptake of, for example, Sestamibi).

An aspect of some embodiments of the invention relates to distinguishingafferent nervous activity from efferent nervous activity. In someembodiments of the invention, imaging of nerve tissue, such as synapsesand/or ganglions at two points along a conduction pathway of a nervoussystem, is provided, while a portion of the nervous system not betweenthe two points is stimulated. The order and/or intensity with which thetwo imaged points are affected by the stimulation may indicate whetherafferent or efferent nerves are being stimulated and/or their specificpathways (e.g., connection network along which simulation point lie)and/or locations (e.g., confirm the location of nerves at thestimulation point and/or locate nerves connected to the stimulationpoint). For example, afferent nerves, when stimulating an organ, forexample, the heart, the intestines, the eye, the bladder, smooth muscle,or other organs, will light up (show increased uptake of radioactivetracers) in the synapses compared to the baseline state (e.g., the statebefore stimulation). Optionally, nervous circuits and/or conductionpathways may be identified by noting the order of excitation of nervoustissue and/or its discrete location with respect to the location of thestimuli (e.g., central or peripheral). The distinction between afferentand efferent nerves may be based on combined anatomical and functionalimaging data, and/or on methods for locating the position of nervestructures, as described herein. For example, the location of thestimulated nerves may be displayed on an anatomical image.

Some embodiments of the inventions may include imaging synapsedistribution using a single photon emission computed tomography (SPECTand/or the use of radiolabeled metaiodobenzylguanidine (mIBG) tracer oranother imaging agent in such imaging.

An aspect of some embodiments of the invention relates to diagnosisand/or therapy control based on synapse distribution in an organ (e.g.,in the heart).

In some exemplary embodiments of the invention, abnormal synapsedistribution and/or activity may be determined by comparing thedistribution imaged with one or more sets of expected or “normal”distributions. Optionally, different expected distributions may beprovided for comparison in different situations, such as per gender,age, nationality, disease state, medication, stress, exercise, stimulusor stimuli. Optionally, a disease may be identified based on a matchbetween the imaged distribution and/or activity and one or more sets ofdistributions characterizing diseases and/or conditions. Optionally,reference sets of synapse distributions characterizing diseases and/orconditions may be acquired for a range of patients. Similarly, referencesets of synapse distributions characterizing healthy people may beacquired for a range of healthy people. A set of distributions imagedfrom a particular patient may be compared with one or more referencesets for diagnosing the state of the particular patient. Such comparisonmay be based on characterization of the reference sets and the setimaged from the particular patient, for example, by relativeintensities, location and/or sizes of hot-spots (e.g., areas ofrelatively higher intensity indicating activity of nerves) and/orintensities, location and/or sizes of cold spots (e.g., areas of lowerintensity, indicating lack of activity or lower activity of nerves).

In some cases, synapse distribution (e.g., density) may teach about adisease process and/or about any remodeling that the nervous system maybe undergoing or gone through. It is important to note that in manypatients, the nervous system is highly dynamic in nature and the densityand activity of the system and the system components (e.g., ganglia,synapses, sympathetic, parasympathetic, efferent and afferent) respondto the disease and to the response of the body as a result of thedisease or a therapy. In some embodiments, the disease and/or state maybe identified based on a change in nervous tissue between two imagingsessions and/or taking into account treatment provided in the interim.

In some embodiments of the invention, diagnosis may take into accountboth distribution and activity of synapses in the imaged region. Forexample, synapse distribution may indicate potential reactivity ofinnervated tissue, and synapse activity may show the degree ofutilization of that potential. The combination of distribution andactivity may also show the evenness of innervation and/orstimulation/control of the tissue by the nerves, for example, the heartby the imaged portion of the neural system.

In some embodiments of the invention, diagnosis may be used to estimatedamage and/or prognosis of healing from a cardiac infarct. For example,it is sometimes the case that damage to nervous tissue is different fromdamage to cardiac muscle and/or that nerve regeneration is different indifferent tissues and/or for different nerve types. Imaging of the heartmay indicate, for example, portions of the heart which are not suitablyinnervated and thus may be the cause of cardiac chamber remodeling,mitral regurgitation, heart failure and/or cardiac dis-synchrony.

In some embodiments of the invention, the effect of a treatment meant toaffect nervous tissue, such as beta blockers and/or renal (or other)denervation, may be measured and/or tracked, optionally by comparingnerve activity to response (e.g., mechanical, electrical, chemical) ofthe organ (e.g., for heart: amount and/or velocity of wall movement).Optionally, the treatment may be modified, e.g., stopped, continued,increased and/or changed, based on the measurements.

In some embodiments of the invention, the effect of a chronic conditionsuch as, for example, hypertension, diabetes and/or stress may betracked by tracking one or both of synapse distribution and/or activity,optionally in conjunction with ganglion activity and/or cardiacresponse.

In some embodiments of the invention, the functional measurements and/ordiagnosis described herein may be used to select placement for pacemakeror other cardiac electrical controller electrodes. For example,electrodes used for arrhythmia treatment may be optionally placed wherethey can subdue, dampen and/or capture more highly activated tissue.

In another example, pacemaker electrodes may be placed according to anexpect effect of the electrical stimulation on nervous activity and/orconductions. In another example, electrodes may be placed so as to blockconduction of stimuli from one area to another area and/or to reducereactivity of cardiac tissue according to over-activity of nervoustissue.

In other examples, the functional measurements may be used to guideablation of nerves fibers, ganglions and/or the outer surface of anorgan—e.g., the heart. Optionally, measurement may be applied afterablation (possibly during an ablation procedure) to determine an effectof ablation and optionally repeat or modify as needed.

In some embodiments of the invention, the functional measurement may beused to select locations for drug eluting patches which elute, forexample, stimulating or inhibiting chemicals to the heart and/or nervoustissue and/or which elute materials which encourage growth of nervoustissue.

In some embodiments of the invention, diagnosis may include identifyingparts of an organ (e.g., the heart) which do not react as desired whenan increase in demand is placed on the organ, for example, based onreduced activity and/or reduced mechanical reaction. In some embodimentsof the invention, a map showing delay in activation time and/orconduction velocity may be correlated with nerve activation. Such acorrelation map may be used to identify, for example, locations whichare over activated in an attempt by the heart to compensate for delayedactivation and/or conduction problems. In some embodiments of theinvention, a therapy may include balancing (or changing the balance in adesired way) the activity of certain regions for example, by modulatingthe neural tissue input and/or or affecting the underlying or associatedheart condition.

In some embodiments of the invention, such functional measurements maybe used to assess causes for hypertrophy and/or hypotrophy in some orall of the innervated organs. For example, patients with rightventricular heart failure may present compensatory neural activation ofthe weaker tissue, which in some cases will have a spillover effect onthe normal tissue. Neural activity beyond a certain level will cause areduction in heart activity that can be treated by local blockade of theimproper increase in compensatory neural stimulation. Such spillover mayalso be implicated, for example, in arrhythmia.

An aspect of some embodiments of the invention relates to a method ofdetecting or localizing ganglions in functional (e.g., SPECT) data. Themethod may include viewing and/or analyzing (e.g., by a processor)functional data at multiple resolutions (e.g., different sizes of imagemasks as described below) and/or object filter sizes (e.g., selectingobjects above a minimum size threshold), and identifying as gangliathose objects which appear in multiple sizes of filters. One or moreparts of the method may be automatically performed by hardware and/orsoftware. Some embodiments of the invention relate to a method ofdetecting ganglions by using an imaging agent, for example, radiolabeledagents, for example, a metaiodobenzylguanidine (mIBG) tracer, or othersuitable imaging agents.

According to some embodiments of the present invention, there areprovided methods and systems of localizing or detecting a nervoustissue, for example ganglia, based on functional imaging modality data(e.g., functional image), optionally in combination with anatomicalimaging data (e.g., anatomical data), for example before and/or duringand/or after a treatment procedure (e.g., heart treatment procedure).

Nervous tissue areas, such as the ganglia, are relatively small andhaving a limited uptake of an imaging agent in relation to surroundingtissues. The combination of functional (e.g., SPECT) data withanatomical data may allow selecting regions of interest (ROIs) thatlimits the area from which data for reconstruction (e.g., data forlocalizing or detecting a nervous tissue) may be gathered. The ROIs maybe selected based on the anatomical data. Such a selection may increasethe signal to noise ratio (SNR) as noises from surrounding tissues arefiltered. The anatomical data is optionally gathered using other imagingmodalities, such as CT, MRI, fluoroscopy modality, Ultrasound, and/orthe like. Additionally or alternatively, one or more anatomiclandmark(s) may be detected from an analysis of the SPECT data, forexample based on the uptake and/or the uptake rate of the imaging agentwhich is set to be engulfed by the nervous tissue and/or by an imagingagent not engulfed by the nervous tissue. The detected anatomiclandmarks may be used for registration with an anatomical image.Optionally, dynamic behavior of the imaging agent during a monitoringperiod may be used as a differentiator of the location of the nervoustissue. In some embodiments, the functional data (e.g., SPECT data) mayinclude kinetic data which is indicative of an uptake rate during amonitoring period, for example in one or more ROIs in a target intrabodyvolume. For example, the SPECT data may include functional data acquiredby monitoring an uptake rate of an imaging agent such as a radio labeledmetaiodobenzylguanidine or a cocktail that includes radio labeledmetaiodobenzylguanidine.

Optionally, the functional (e.g., SPECT) data may be combined withanatomical data captured during an ablation procedure, for exampleduring denervation of ganglionic plexi in proximity to the atria of apatient's heart, renal denervation, a liver treatment, a spleentreatment, and/or an intestine treatment. Optionally, the functionaldata may be combined with anatomical data for diagnosis, for example fordetermining whether to perform a heart treatment such as neuralmodulation or ablation for treatment of different disease statesincluding heart arrhythmia, congestive heart failure and ischemic heartdisease.

Optionally, functional (e.g., SPECT) data may be captured in advance andforwarded to a workstation for combination with anatomical data, forexample during and/or before a treatment procedure, e.g., a hearttreatment procedure. For example, the combination may be performed usinga CartoMerge™ module. Optionally, SPECT data and anatomical data, suchas fluoroscopy data, are combined for performing a catheterizationprocedure, allowing an operator to identify and/or localize targetnervous tissue and optionally to navigate and/or guide a treatment probeto proximity with the target nervous tissue (e.g., to contact the targetnervous tissue). The treatment probe may be, for example, an ablationdevice, for example an intraoperative ablation device, a non invasiveablation device, and/or a minimally invasive ablation device.Alternatively or additionally, the treatment device may include an RFprobe, magnetic-based catheter and/or a Cryosurgery probe.

In some embodiments, functional data and anatomical data, may becombined for performing a catheterization procedure, allowing anoperator to navigate a treatment probe or an imaging probe.

In some embodiments, functional data may allow localizing tissue (e.g.,nerve structures) that cannot be localized by anatomical imaging alone.For example, hidden functional portions of an organ may be localized byvisualizing their functionality. In some embodiments, this may becombined with enhancing the resolution of functional imaging, forexample, by focusing the functional imaging on regions expected toinclude the anatomical imaging hidden functional portions. These regionsmay be identified, in some embodiments, based on structural imaging.

Optionally, anatomical data is used for instructing the reconstructionsof functional (e.g., mIBG) activity mapping functional images in amanner that the resolution of areas wherein the nerve structures (e.g.,GP, ganglia) are located is increased. Optionally, reconstruction isperformed with anatomically varying gating, for example, anatomicallyvarying image masks.

For example, nervous tissue in the atria, such as individual ganglia,are commonly surrounded by fatty connective tissue closely adjacent toepicardial muscle. Other ganglia in the atria are imbedded in the fatpad overlying the posterior surface of the left atrium and/or in theatrioventricular groove. The close proximity of these ganglia to a fatlayer may prevent an operator (manually) or a processing module(automatically) from localizing the ganglia based on the anatomicaldata. The combination with the functional data provided by the SPECTdata (for example) however, may allow separating between the ganglia andthe surrounding tissues based on the uptake rate of the imaging agent,kinetic data and/or dynamic behavior.

Optionally, the nerve structure (e.g., GP) is identified, rather thanthe fat pad. Optionally, the nerve structure itself is identified withinthe fat pad, rather than identifying the fat surrounding pad.Alternatively or additionally, the fat pad is used as an anatomicalguide for detecting the GP within the fat pad, for example, withreference to the image mask method described below (e.g., FIG. 2B),image masks may be generated using anatomical images to correspond withthe fat pad. The GPs within or next to the fat pads are then identifiedwithin functional data based on the application of the image masks tothe GP.

Optionally, during ablation, the GP within the fat pad is targeted forablation. Optionally, the ablation is selected to ablate the GP, ratherthan the surrounding fat pad. The surrounding fat pad may not beentirely removed, for example, most of the fat pad may remain, or someof the fat pad, for example, no more than about 25%, or about 50%, orabout 70%, or about 90% of the fat pad. The fat pad ablation may beperformed as required to ablate the GP inside and/or near the fat pad.The entire fat pad may be removed, for example, as a secondary effect ofablating the GP, rather than being the primary target.

An aspect of some embodiments of the present invention relates to amethod of processing functional images to identify and/or locate nerves(e.g., GPs) within tissues (e.g., heart, stomach, intestines, kidney,aorta, or other organs or structures). Optionally, anatomical imagesused to reconstruct the functional image and/or process the functionaldata are combined with the functional images, the combined image may beused as a basis for locating GPs. The method may comprise generatingimage masks corresponding to regions of the anatomical image contain theGPs and/or the innervations of the organ. The GPs are not visible on theanatomical image, for example, cardiac GPs on a CT scan that includesthe heart. The selected image masks are applied to correspondinglocations on the functional image, for example, by a registrationprocess. GP characteristics within the functional image arereconstructed, instructed by the applied mask. GPs within the selectedimage mask applied to the functional image may be identified, based onpredefined rules, for example, size of active spots and/or intensity ofthe active spots relative to surrounding intensity (e.g. relative to anaverage value). In this manner, anatomical information is used forreconstructing the activity of GPs within the functional image. Theanatomical information, in the form of the mask, may be used for guidingthe processing to certain regions of the functional image, to help inlocating the GPs of interest. The identified GPs may be displayed on theanatomical image or a combined functional and anatomical image, and/ormay be registered with a navigation system for patient treatment such asan electrophysiological catheter navigation system for treating diseases(e.g., cardiac disorders such as arrhythmias). In this manner, theanatomical image may serve as a guide for where to look within thefunctional data to identify the relevant nerve structures, where therough location of the nerve structure within the body is known beforehand, for example, based on a predefined anatomical atlas.

Optionally, the image mask method may be used to decide where theinnervated organ is located and/or to define where to look for objectsof interest.

The size and/or shape of the image masks may be defined, for example, bythe ability of software to segment the anatomical image, by theresolution of the anatomical and/or functional images, by the resolutionof the ablation treatment, by the size of the structure beingidentified, or other methods.

The image mask method is not limited to detecting nerve structures (e.g,GPs). The image mask method may be used to detect other smallstructures, for example, small cancer lumps and/or lymph nodes neartissue.

Optionally, image masks are generated for an organ with one or morelumens, fluid and/or air filled and/or potential spaces (e.g., bladder,heart, stomach, intestine, aorta). Optionally, the image masks aregenerated to identify structures (e.g., nerves, GPs) in the tissueitself, rather than within the lumen and/or space. Optionally, thecontour of the organ and/or tissue is identified based on the anatomicalimage, for example, the inner wall of the heart chambers, stomach,bladder, aorta, or other organs. Optionally, the image masks aregenerated based on the anatomical image, to guide searches within thefunctional data to identify the nerve structures.

For purposes of better understanding some embodiments of the presentinvention, as illustrated in FIGS. 2-47 of the drawings, reference isfirst made to the anatomy and function of an autonomic nervous system(ANS) of a mammal (e.g., human) as illustrated in FIG. 1. FIG. 1 showsthe components of an ANS 1000, in schematic form. As can be seen, theANS includes a network of ganglions, also termed ganglionic plexi (GP).Nerve fibers meet and synapse at the ganglions.

The human body has several control systems, including the hormonalsystem, the central nervous system and the autonomic nervous system(ANS). As traditionally depicted, the autonomic nervous system is(mostly) not under conscious control and serves to regulate various bodyfunctions, including, life sustaining functions. For example, basalheart rate, breathing and digestion are controlled by the autonomicnervous system. In some classifications, the portion of the autonomicnervous system which relates to digestion is termed the enteric nervoussystem (ENS).

A spinal column 102 provides both sympathetic and parasympatheticenervation. As shown, parasympathetic enervation 106 may proceeddirectly to organs 114 and/or to secondary ganglia 110. Sympatheticenervation may be modulated by a spinal ganglia and then feed intosecondary ganglia 110 or organs 114. In many cases, the sympathetic andparasympathetic enervations interact at the secondary ganglia 110 (e.g.,Ciliary, Celiac, etc.). Secondary ganglia 110 may be connected directlyto nerve endings at an organ (e.g., 114). In some cases, an intermediarynetwork or chain of ganglia exists as well (not shown).

The ANS is generally considered to include two main functional layers,the sympathetic nervous system (SNS), generally in charge of excitatoryand increased responsiveness and control and the para-sympatheticnervous system (PNS), generally in charge of damping responsiveness andcontrol. For example, heart rate is increased by increased activity ofthe SNS and decreased by increased activity of the PNS. In some organs,such as the heart, the nerve fibers of the SNS and nerve fibers of thePNS meet at certain ganglions. Ganglions which include both SNS fibersand PNS fibers utilize a balance between the excitations of the SNS andPNS to determine their behavior.

The ANS includes both afferent (leading towards the innerverated tissue)and efferent fibers (leading away from the innerverated tissue).

From a perspective of diagnosis, it is recognized that malactivity ofthe ANS may cause body dysfunction, for example, in atrial fibrillation.Furthermore, general ANS tone is considered to be related to somediseases such as high blood pressure. Damage to the ANS can sometimesoccur, causing organ dysfunction, for example, in transplanted organs.

From a perspective of treatment, some examples of treating an undesiredcondition by ablating a part of the ANS have been suggested.

It is noted that throughout the application, the term GP and/or gangliamay also refer to a synaptic center, to encompass regions other thanganglia (such as where a nerve meets an organ), as it may be difficultto differentiate between a ganglion and a GP. In some cases, thedifference between an individual ganglion and a synaptic centercomprising a plurality of ganglia (e.g., a ganglionated plexus) ismerely semantic (e.g., wherein different people in the art use differentterminology) and/or of no significant medical importance.

Before explaining at least one embodiment of the invention in detail, itis to be understood that the invention is not necessarily limited in itsapplication to the details of construction and the arrangement of thecomponents and/or methods set forth in the following description and/orillustrated in the drawings and/or the Examples. The invention iscapable of other embodiments or of being practiced or carried out invarious ways.

Reference is now made to FIG. 2A, which is a flowchart of a method oflocalizing and/or detecting and/or identifying, for example imagingand/or mapping, nervous tissue in an intrabody volume by combiningfunctional data (e.g., SPECT data) and optionally anatomical data,according to some embodiments of the present invention. It is noted thatin some cases, localization, detection and identification are usedinterchangeable, for example, when referring to generating data denotingthe position of nerve structures. In other cases, localization,detection and identification are not interchangeable, for example, withreference to FIG. 2B, during the process of generating the data of theposition of the nerve structures, in which case the terms may denotedifferent stages of the process.

Optionally, method 200 includes a method of treating a patient based onthe localized and/or detected nervous tissue. Optionally, at least someblocks of method 200 are computer-implemented. Optionally, at least someblocks are performed manually by an operator. Reference is also made toFIG. 3, which is a system 500 for localizing and/or detecting nervoustissue and/or other ANS components in an intrabody volume by combiningfunctional data and anatomical data, according to some embodiments ofthe present invention. One or more blocks of the method of FIG. 2A maybe performed by system 500 of FIG. 3, for example, one or more modules502 corresponding to parts of the method. Optionally, system 500 or oneor more components of system 500 is an image data processing unit.

Optionally, the method and/or system are integrated with a navigationsystem, for example, the CARTO® system manufactured by BiosenseWebster®, and/or the MediGuide™ System manufactured by St. JudeMedical™. The navigation system may perform one or more of the followingfunctions: map electrical activity in the heart, show where ablation wasperformed, allow navigation (e.g., of the treatment catheter) to wherethe map directs to get to in order to ablate, navigate around the pointindicated on the mat to further pinpoint the GP. Optionally, one or moreblocks of the method of FIG. 2A (e.g., related to the treatment) aredriven by the navigation system (e.g., CARTO® system). The treatment maybe performed using the navigation system, to ablate nerve structuresidentified using the systems and/or methods described herein. Forexample, the coordinates within the CARTO® system space corresponding tothe target nerve structures are provided by the system and/or methoddescribed herein. Alternatively, navigation is performed underfluoroscopic imaging (or other imaging) and the map that shows functionand/or anatomy.

System 500 may include one or more modules 502 having instructions forexecution by a processor 504. In some embodiments, one or more modules502 may be integrated within processor 504. Modules 502 may containprogram instructions for execution of one or more blocks of the methodof FIG. 2 or other methods described herein. Modules 502 may be storedon a non-transitory computer readable medium such as memory 506.

As used herein, the term “processor” or “module” may include an electriccircuit that performs a logic operation on input or inputs. For example,such a processor/module may include one or more integrated circuits,microchips, microcontrollers, microprocessors, all or part of a centralprocessing unit (CPU), graphics processing unit (GPU), digital signalprocessors (DSP), field-programmable gate array (FPGA) or other circuitsuitable for executing instructions or performing logic operations.

The instructions executed by the processor/module may, for example, bepre-loaded into the processor or may be stored in a separate memory unitsuch as a RAM, a ROM, a hard disk, an optical disk, a magnetic medium, aflash memory, other permanent, fixed, or volatile memory, or any othermechanism capable of storing instructions for the processor/module(e.g., memory 506). The processor(s)/modules may be customized for aparticular use, or can be configured for general-purpose use and canperform different functions by executing different software.

If more than one processor is employed, all may be of similarconstruction, or they may be of differing constructions electricallyconnected or disconnected from each other. They may be separate circuitsor integrated in a single circuit. When more than one processor is used,they may be configured to operate independently or collaboratively. Theymay be coupled electrically, magnetically, optically, acoustically,mechanically or by other means permitting them to interact.

Optionally, one or more processor(s) 504 are in electrical communicationwith a functional imaging modality 508. Optionally, processor 504 is incommunication with an anatomical imaging modality 510.

Optionally, processor 504 is in electrical communication with a datarepository 512, for example, for storing data of the detected nervoustissue, and/or other processing results.

Optionally, processor 504 is in electrical communication with anavigation system 514, for example, for navigating a catheter inside thevasculature of a patient. The operator of navigation system 514 maynavigate the catheter based on the detected nervous tissue. Optionally,navigation system 514 is an electrophysiological (EP) navigation systemfor the heart, or another navigation system for other regions of thebody.

Optionally, processor 504 is in electrical communication with one ormore output elements 516, for example, a graphical user interface (GUI),a screen for displaying images, a printer, or other output devices.

Optionally, processor 504 is in electrical communication with one ormore input elements 518, for example, a keyboard, a mouse, a graphicaluser interface (GUI), a touchscreen, a microphone for voice recognition,or other input devices. Input elements may be configured to receiveinputs from system 500 operator, e.g., a physician.

Optionally, processor 504 is in electrical communication with a network520, for example, the internet, a local hospital network, a distributedclinical network, or other networks. One or more remote servers mayperform some or all of the processing, may store data, may provideupgrades, and/or may be used by remote operators.

Components of system 500 may be sold together and/or in parts. Forexample, modules 502 may be sold as software for installation on anexisting workstation, for example, downloaded from network 520 and/orprovided on memory 506. In another example, processor 504, memory 506,and modules 502 are sold together, for example, as a workstation. Inanother example, the complete system is sold.

In some embodiments, components of system 500 may be provided atdifferent locations and/or as separate devices, e.g., data of thedetected nervous tissue may be obtained by module(s) 502, stored on datarepository 512 and send to navigation system 514. The data of thedetected nervous tissue may be obtained before the treatment starts.

As used herein, the functional data (e.g., SPECT data) may be a SPECTimage captured by a suitable SPECT modality, for example,electrocardiogram-gated SPECT (GSPECT) modality, A-SPECT, SPECT-CT,and/or D-SPECT™ of Spectrum Dynamics modality. The specifications ofthese modalities are incorporated herein by reference.

As used herein, the phrase nervous tissue means Ganglia (i.e.,ganglionic plexi, GP), neural fibers, neural synapses, neural subsystems, and/or an organ specific nervous tissue. Examples of neuralsubsystems include, a peripheral subsystem, and/or an autonomic subsystem, such as the sympathetic and the parasympathetic autonomic subsystems. Examples of organ specific nervous tissue may include, acarotid body, aortic arch, pulmonary, renal, splenic, hepatic, inferiormesenteric, superior mesenteric, muscular and/or, penile nervous tissue.It should be noted that the localization or detection may be performedwith and/or without reconstruction of an image based on the functionaldata. For example, localization or detection may be performed byidentifying an imaging agent signature, in the functional data withoutreconstructing the functional data to form a spatial image.Nevertheless, an image reconstructed from the functional data may beanalyzed to localize and/or detect the nervous tissue. In suchembodiments, the functional data may be processed to identify an imagingagent signature of a target nervous tissue. This target tissue signaturemay be indicative of the location of the target nervous tissue. Theimaging agent signature may include kinetic information, uptakeinformation of one or more imaging agent(s), washout information of oneor more imaging agent(s), and/or one or more combination(s) thereof. Thetarget nervous tissue signature may be measured relative to a backgroundin an intrabody volume (e.g., as provided by an image mask) and/or usingpreviously captured functional data of most probable location, number,size, and/or the like.

Referring back to FIG. 2A, optionally, at 202, a patient is selected fordisease screening, evaluation and/or treatment based on identificationof nervous tissue. Optionally, the patient is selected based on ahypothesis that the patient is suffering from improper activity of theANS, for example, over activation and/or improper activation.Optionally, the patient is selected based on a hypothesis that thepatient may be treated by ablation or injection of a therapy, and/orother therapies of the identified portions of the ANS. For example, thepatient may be suffering from atrial fibrillation (AFIB) secondary toimproper activity of the ANS innervating the heart. The patient may beselected, for example, manually by a physician and/or automatically bysoftware, for example, software that detects one or more inclusioncriteria within the electronic medical record of the patient.

Optionally, at 204, the selected patient is referred to an imagingclinic for obtaining images or other data for detection of the nervoussystem (e.g., for identifying one or more components of the ANS—such asGPs).

Optionally, at 206, anatomical data which optionally includes anatomicalimages, for example fluoroscopy images, of an intrabody volume of apatient (e.g., a patient organ) on a patient surface and/or volume maybe captured, e.g., by using an anatomical imaging modality (e.g.,modality 510), such as a fluoroscopy modality, CT and/or otheranatomical imaging modalities. For brevity, the term anatomical data mayinclude locational data of an intra-body treatment probe and/orlocational data gathered using an intra-body treatment probe. In suchembodiments, the combination of data may be used to guide a treatment inreal time.

Optionally, anatomical images are acquired to contain multiple framesduring a dynamic cycle, for example, during the cardiac cycle.Optionally, additional synchronization data is collected for correlationwith the dynamic cycle, for example, an electrocardiogram (ECG).

Optionally, synchronization data collected for correlation with thedynamic cycle is used to better match intensity readings of thefunctional data to tissue structures (e.g., to the heart wall).Optionally, the image mask method of FIG. 2B may be used with thesynchronization data. Optionally, in the case of a single anatomicalimage (obtained at some point during the cycle) the model allowsmigration of the detected intensity points to the relevant tissue points(e.g., nearby heart wall). For example, the heart wall moves during thecardiac cycle. Functional data may appear within the heart chamber, eventhough the intensity is actually related to GPs in the nearby wall. Forexample, sestamibi data may be migrated mIBG data that is co-registeredwith the sestamibi data may be migrated. The migrate may provide forboth data registration and image construction.

Optionally, at 208, functional data is collected from the patient by afunctional imaging modality, for example, functional imaging modality508.

The anatomical imaging (block 206) and functional imaging (block 208)may occur at different times or may be performed simultaneously at thesame time.

Optionally, functional and/or anatomical images are acquired to containmultiple frames during a dynamic cycle, for example, during the cardiaccycle. Optionally, additional synchronization data is collected forcorrelation with the dynamic cycle, for example, an electrocardiogram(ECG).

A patient may be injected with an imaging agent, for example aradioactive tracer and/or a combination of radio tracers, such as aradio labeled metaiodobenzylguanidine (mIBG) and/or a combinationthereof with one or more other radioactive tracers, such as TC and mIBGand TL and mIBG For example, a cocktail for simultaneous isotopeacquisition with I-123 mIBG, I-124 mIBG, and/or Tc-99m Technetium(99mTc) sestamibi (Mibi) tracers. The imaging agent may be engulfed tobe taken by a specific target pathologic tissue, for example cancerouscells. Combination of the mIBG with other radioactive tracers may give alocalizing or monitoring or imaging information.

A functional modality (e.g., SPECT) having one or more radiationdetectors may be used to acquire functional data (e.g., SPECT data), forexample a SPECT image, of the intrabody volume. The imaging agent mayallow localization of specific sites according to imaged uptake rates.For example, mIBG has an affinity for adrenergic nerves, for example toGPs, see Shankar Vallabhajosula et al., PhD, RadioiodinatedMetaiodobenzylguanidine (MIBG): Radiochemistry, Biology, andPharmacology, Semin Nucl Med 41:324-333, which is incorporated herein byreference.

Optionally, functional data such as SPECT data of the intrabody volumemay be acquired using a SPECT modality. The SPECT data may be takenusing an exemplary SPECT modality that includes a set of collimators,for example scale division (SD) collimators. Optionally, between 10 and20 collimators are used, for example 14. Optionally, the SPECT modalityscan pattern includes about 360 positions around 360 degrees.Optionally, the used reconstruction algorithm is ordered-subsetsexpectation maximization (OSEM) and/or depth-dependent resolutionrecovery (RR). Optionally, the pixel size is between about 2.5millimeter³ and about 4.9 mm³.

In some embodiments, the functional or anatomical data or image iscaptured before an invasive medical procedure begins, for example beforethe patient enters a catheterization laboratory (CathLab) room. Forexample, aSPECT data or image is introduced to a workstation before thecatheterization process.

The functional data and the anatomical data may be acquired during amedical procedure, for example a diagnosis or a treatment procedure, forinstance a catheterization process, for example as described here.

Optionally, the functional data provides indicators of one or more ofthe individual tracer uptake, total tracer uptake, tracer uptake rate,blood flow, fractional flow reserve in a blood vessel, tracer washout,areas which are above a predefined threshold (e.g., static and/ordynamic threshold) such as above surrounding average values, and/or thelike. Optionally, the functional data is produced per segment of a fewcentimeters in dimension.

Optionally, functional data is reconstructed with a certain resolutionalong the wall, for example, along the inner surface of the chamber.Alternatively or additionally, functional data is reconstructed with acertain resolution along the thickness of the wall. The two resolutionsmay be similar or different.

Optionally, the functional data is reconstructed at a quality resolutionof about 1 cm×1 cm×1 cm or better, for example 7 mm×7 mm×7 mm or better,5 mm×5 mm×5 mm or better. Optionally, the functional data isreconstructed in a non-cubical voxels structures. Optionally, thefunctional data is reconstructed in voxels which are aligned with amodel of the imaged object (such as the heart's muscle wall geometry),and/or a combination thereof.

Optionally, one or more ROIs are identified in the functional data, forexample based on the implied and/or indicated mIBG uptake, a size and/orshape of segments in the functional data, for example based on a matchwith one or more reference items, for example predefined models of therespective ROI(s) and/or by filtration of known organ(s), such as theventricle. Additional details of identifying ROIs are described herein,for example, with reference to FIG. 2B. Optionally, one or more ROIs areidentified by the anatomical image, e.g., by defining one or more imagemasks.

Optionally, the uptake rate of the radiotracer (e.g., mIBG) is measuredand analyzed with reference to the respective ROI in which a GP islocated, for example based on anatomical imaging data, for example asdescribed below. When the ROI is indicative of a location that includesganglia, the uptake is optionally used as an indication about thephysiological condition of the ganglia.

In some embodiments, anatomical segmentation of ROIs in areas of theatria may allow separately analyzing different atrial uptake activities,differentiating between uptake activities of different ROIs in theatria, and not only the uptake activity of the atria as a whole. Forexample, anatomical input from an anatomical imaging source may be usedto associate different segments of a SPECT image with different organsor tissues, for example, one segment of the SPECT image may beassociated with the atrial muscle wall (e.g., myometrium), and anothersegment of the SPECT image may be associated with the atrial epicardium.According to some embodiments of the present invention, the ROI(s)includes one or more ganglia. Optionally, a dynamic behavior of theimaging agents during a monitoring period in the ROIs is analyzed toidentify differentiator(s) for separating a target location fromsurrounding tissues. The dynamic behavior is optionally matched with oneor more predefined patterns and/or set of rules to identify a targetsite for treatment, for example for ablation.

Optionally, at 210, the anatomical data and the functional data may becombined to allow locating or detecting the nervous tissue, for example,by a combination module 502A. Detection of GP is optional. Optionally,GPs are not looked for when imaging the nervous system and/or otherstructures. For example, anatomical data and the functional data may becombined to obtain a combined anatomical-functional image, e.g., theimage may contain two layers—anatomical and functional. The image may beof the entire organ or a part thereof. The combinedanatomical-functional image or data may be presented to the operator,e.g., by output element 516. The combined anatomical-functional image ordata may be sent to processor 504 for further processing—e.g., toidentify one or more ANS components thereof.

Optionally, at 212 ganglions are located, for example, by a locatingmodule 502C. Possible locations may be identified. Functional behaviorof ganglions may be extracted. Optionally, an ANS map and/or image ofthe target organ is generated. The ANS map may include the locations andoptionally size and activity levels of one or more ANS components. Theidentified nervous tissue may be presented on an anatomical image toshow possible locations, as the actual location of the GP may beuncertain, instead showing several alternatives and/or a density map.For example, colored on a black and white image. Co-ordinates may beprovided with reference to a navigation tool (e.g., catheter).Optionally, selected parts of the nervous tissue are identified and/orlocated, for example, based on a local size above a predefinedthreshold, based on local functional activity, and/or other predefinedrules. In some embodiments, an image per se is not generated but ratherANS data of the identified nervous tissue may be generated—e.g., filecontain identified nervous tissue information such as: location, sizeand/or activity level.

The number of GPs identified, is for example, 1, 2, 3, 5, 8, 10, orother intermediate or larger numbers, or, 2-6, or 3-8, or 4-10, or otherranges. The size of GPs identified is, for example, about 2 mm×2 mm×2 mmto about 4 mm×4 mm×4 mm, or about 1 mm×1 mm×1 mm to about 3 mm×3 mm×3mm, or other smaller, intermediate or larger sizes.

The ANS image or data may be of the entire organ or a part thereof. TheANS image or data may be presented (or otherwise provided) to theoperator, e.g., by output element 516. The ANS image or data may be sentto navigation system 514 and/or stored on memory 506 for future use.

According to some embodiments of the present invention, functional datamay be combined with anatomical data for localizing ganglionic plexi(GPs), for example: in the atria. This may allow guiding a medicalprocedure, for example to use anatomy to tell where the catheter islocated, and use the functional data to identify targets. For example,the localization may allow guiding an operator to operate an ablationunit located at the tip of a catheter.

Reference is now made to FIG. 2B which is a flow chart of a method forprocessing functional images to identify and/or locate one or more ANScomponents (e.g., ganglions) (may correspond to block 212), inaccordance with some embodiments of the present invention. It should benoted that method of FIG. 2B is not limited to identification and/orlocalization of ANS component(s), for example: it may be used forextracting other information from functional and anatomical images ordata based on application of image masks, for example, as will bediscussed below.

Optionally, the method may combine the functional and anatomical images(may correspond to block 210). Alternatively, the anatomical image mayprovide a basis for reconstructing selected parts of the functionalimage that contain the GPs. The method may be performed, for example, bydata combining module 502A and/or processor 504 of FIG. 3, an image dataprocessing unit, or other modules and/or systems. The method may useimages from the anatomical imaging modality (which show organ structure,but not GPs in sufficient detail or at all) to reconstruct images fromthe functional imaging modality (which may show ANS components—e.g., GPsor activity level, but not the organ structure in sufficient detail orat all). Reconstructed functional images may show the GPs overlaid onthe organ structure.

Optionally, the method provides (as an output) the general region whereGPs are located. Alternatively or additionally, the method providesregions where the GPs are not located. The precise location of GPs mayvary anatomically between different patients. The specific location ofthe GP may be identified during an ablation procedure, for example,using high frequency stimulation (HFS). Alternatively or additionally,the method provides the precise location of the GP, for example, using acoordinate system. In some embodiments, there may be a minor deviationfrom the GP actual location (e.g., due to noise in image, registration)to the location of the GP which provided by the method which may becorrected by the operator during the ablation procedure.

Optionally, the functional activity (e.g., mIBG activity) is identifiedin preselected tissue regions. The image masks are defined based on thepreselected tissue regions within the anatomical image that correspondto the functional activity that is being detected. For example, in theheart, GPs are located within the heart wall or nearby, and/or in fatpads. Optionally, the fat pad size and/or shape is used to define thesearch window and/or image mask. Distribution of mIBG within a fat padmay be of interest, with or without GP detection. Image masks aredefined for the anatomical image to look for the GPs within the heartwall or nearby. The generated image masks are then applied to thefunctional data, to identify the GPs based on activity within themask—e.g., within the heart wall or nearby.

Optionally, the reconstruction is directed to anatomical regions wherefunctional activity (e.g., from GPs) is expected, for example, based ona predefined anatomical atlas, for example, based on the location of GPsin normal anatomies. Such data may be collected from several patients,for example, by imaging and/or autopsy dissection.

Optionally, the image masks are defined to identify some or all activityof nerves, for example, GPs, synapses, axons, nerve bodies, or othernerve structures and/or different types of nerves. Image masks may bedifferent and/or the same.

In this manner, the image masks may serve a guide for directing theidentification of the nerve structures to certain regions within thefunctional image and/or data. There may be many regions of intensitywithin the functional data, only a small subset of which may be relevantfor identifying ANS components location—for example: to be used inablation. As the rough location of the nerve structures relative to bodyorgans and/or tissues may be known (e.g., by the atlas) but notvisualized on the anatomical image, the search for the nerve structuresmay be directed to the corresponding regions on the functional image.The search may be focused to regions having a large percentage ofintensity readings that denote relevant nerve structures.

The method may be used to detect different types of GPs, at differentlocations of the body (tissues, organs), for example, as describedherein.

The method may improve system performance, by performing calculationswithin the region of interest to identify the neural tissue.Calculations may not need to be performed in regions without neuraltissue.

The method may reduce radiation exposure to the patient. Additionalradiation may be applied to regions containing the neural tissue forimaging to provide higher resolution at the regions. Less radiation maybe applied to regions not containing the neural tissue.

The method may improve analysis results and/or images. Neural tissuewithin selected regions may be analyzed and/or imaged. Neural tissueoutside the selected regions may not be analyzed and/or imaged.Interference and/or image complexity from the neural tissue outside theselected regions may be reduced or prevented. In this manner, neuraltissue that is not contributing to the medical condition of the patientand/or neural tissue that is not a target for ablation therapy may beexcluded from further analysis. Alternatively, the non-targeted neuraltissue may be identified separately from neural tissue targeted forablation.

Optionally, at 4802, functional imaging modality data and/or images arereceived, for example, a D-SPECT image or other images. The images maybe of a body part, for example, a torso, an abdomen, a heart, or otherbody parts (e.g., based on scanning protocols). The body part includesthe nerve tissue to be images and/or the innervated organ, for example,GPs of the heart, intestines or other organs. Optionally, the functionalimages includes regions of activity that denote nerve tissue (e.g., GP),for example, from uptake of the radiotracer (e.g., mIBG).

Optionally, functional data is collected from a body part that hasregions where nerve activity is expected, and regions where nerveactivity is not expected. For example, during imaging of the heart, datadenoting nerve activity is expected from the heart wall and/orsurrounding tissues, and no nerve activity is expected from inside thehollow chambers (containing blood). Noise may be received from areascorresponding to the inside of the heart chamber, even though noactivity is expected. Optionally, the noise is removed from thefunctional data based on the corresponding anatomical image (e.g., afterimage registration). Optionally, intensity denoting noise within blood(or other fluid) filled chambers and/or vessels is removed. For example,intensity readings of the functional data corresponding to heartchambers and/or surrounding blood vessels are removed, e.g., by applyingone or more image mask on functional image.

Optionally, at 4804, an anatomical region is extracted from the image.Optionally, the tissue (which may contain nerve structures) is separatedfrom hollow spaces (which do not contain nerve structures, but maycontain fluid). For example, to image the heart, the wall of the leftventricle (LV) may be extracted. Alternatively or additionally, thehollow space within the LV may be extracted. It is noted that theextracted region may be a layer of tissue, such as the tissue layersforming the LV wall, instead of, for example, the LV including thehollow chamber inside the LV. For example to image the kidney, the wallsof the renal artery may be extracted and/or the inside of the artery maybe extracted. When imaging other organs, dominant portions of the organmay be selected.

Optionally, at 4806, one or more registration cues are extracted fromthe image. The registration cues may be from the organ of interest,and/or surrounding anatomical structures, for example, LV axis, liver,heart septum, RV, torso. Registration cues may be used to matchanatomical images with functional images, and/or to match anatomicalimages during a physiological cycle (e.g., cardiac cycle).

Optionally, at 4808, anatomical image modality data and/or images arereceived, for example, from a CT, MRI, 3D US, 2D US, or othermodalities. The anatomical image denotes the structure of the tissueand/or organ innervated by the nerve tissue (e.g., GP). The anatomicalimage denotes the tissue and/or organ structure corresponding thelocation of the nerve tissue (e.g., GP). The anatomical images maycontain the same nerve tissue to be imaged and/or the same innervatedorgan.

Alternatively, anatomical data is received that is not personalized tothe patient, for example, from a general anatomical model.

Optionally, anatomical data from an anatomical imaging modality isreceived to reconstruct an anatomical image of a region of a body of apatient. Optionally, the region comprises a portion of at least oneinternal body part which borders on a target nerve tissue.

The anatomical images and the functional images denote correspondingregions of the body containing the GPs for identification and/orlocalization. For example, both modalities may take pictures of theheart, kidney, or other organs.

For example, to image GPs of the heart, anatomical and/or functionalimages of the heart are obtained. For example to image GPs of thekidney, anatomical and/or functional images of the kidney, renal arteryand/or aorta are obtained.

Optionally, at 4810, images corresponding to different times during adynamic cycle are extracted and/or acquired. For example, for the heart,images are extracted along the cardiac cycle, for example, the enddiastolic volume (EDV) and/or the end systolic volume (ESV). In anotherexample, for the bladder, images may be extracted for a full bladder andan emptying bladder.

The average image may be computed, for example, (EDV+ESV)/2.

Optionally, at 4812, one or more images are segmented. Segmentation maybe fully automatic and/or may require manual user intervention.

Optionally, at 4814, an anatomical region is extracted. Optionally, theanatomical region corresponds to the anatomical region extracted at4804. Optionally, the anatomical region is extracted from the segmentedimage of block 4812.

Optionally, at 4816, one or more registration cues are extracted fromthe image. The registration cues may be from the organ of interest,and/or surrounding anatomical structures, for example, LV axis, liver,heart septum, RV, torso.

Optionally, at 4818, the functional images or data and the anatomicalimages or data are registered. Optionally, the images are registeredbased on alignment of the extracted anatomical regions of blocks 4804and 4814. Registration may be performed manually, automatically and/orsemi-automatically.

Optionally, the registration is performed to take into account thedynamics of the organ, for example, movement of the heart. For example,anatomical images during the dynamic cycle may be aligned together,and/or functional data may be corrected for the dynamic movement, forexample, intensity readings within the heart chamber may be corrected tothe nearby moving heart wall.

Optionally, at 4820, image masks are generated based on the anatomicalimage and/or data. Optionally, the image masks direct processing and/orvisual display of the nerve tissue to specific locations of the imagelocated within the image masks. For example, GPs are displayed and/orprocessed within the volume of an applied image mask. GPs outside thevolume of the image mask may not be processed and/or displayed. GPsoutside the volume of the image mask may be processed and/or displayeddifferently than those GPs inside the image mask.

Optionally, the anatomical images are processed to generate the imagemask corresponding to dimensions of at least one internal body part, forexample, the walls of the chambers of the heart. For example, dimensionof internal body part of the specific patient may be calculated and usedto define the mask.

Optionally, the image masks are selected and/or defined for tissuesurrounding a hollow chamber, for example, the image masks are definedbased on the shape of the heart chamber walls and do not include thehollow region within the chambers, the image masks are based on theshape of the arterial wall and do not include the hollow region withinthe artery, the image masks are based on the shape of the bladder walland do not include the hollow region within the bladder. It is notedthat the nerve structures may exist within the tissues defined by theimage masks, but may not exist within the hollow spaces (which may befilled with fluid such as blood, urine or other fluids). The image masksmay include tissue surrounding the organ of interest.

The image masks are defined, for example, based on image segmentation(e.g., according to the ability of the system to segment the image),based on tissue types (e.g., muscle vs. connective tissue), based onorgan size, based on sub-structures within the organ (e.g., heartchambers, liver lobes, kidney parts), or other methods.

Different image masks may be generated for different tissue types,and/or for GPs at different locations within the organ. For example, forGPs within the epicardium one set of image masks is generated. For GPswithin the myocardium another set of image masks may be generated. Imagemasks may be generated for fat pads.

The image mask may be a 2D and/or 3D volume with a shape and/or sizeselected based on tissues and/or organ parts within the anatomicalimage. The image mask may correspond to anatomical parts believed tocontain the neural tissue for imaging (e.g., GPs), for example,corresponding to the walls of the four heart chambers, corresponding tothe intestinal wall, bladder wall, renal artery, aortic branch region ofthe renal artery, kidney, or other structures. In some examples, theimage mask may be generated to contain GPs within the epicardial and/ormyocardial tissue of the heart. In another example, the image masks maybe generated to contain kidney innervating GPs at the aorta-renal arteryjunction. It is noted that the image masks may be generated based on anestimated location of the GPs (e.g., normal patient anatomy), as the GPsmay not be visible on the anatomical image. The image masks may begenerated based on an estimated location of the GPs and based ondimension of internal body part as may be inferred from the anatomicalimage.

Optionally, the generated image masks correspond to the segments of theanatomical image. For example, the heart is segmented into some chamberwalls (e.g., having the GPs for ablation), and the generated image maskscorrespond to the chamber walls of interest.

For example, a first image mask is generated for the walls of eachchamber of the heart. It is noted that the thickness of smaller chambersmay be difficult to measure in certain images (e.g., CT). In such cases,the thickness of the first image masks for each chamber may be based ona measurable anatomical region such as the LV. Alternatively, thethickness of the chamber is measured using another imaging modality(e.g., US, MRI) and/or estimated. The measurement may be performed usingthe anatomical image, for example, the thickness for the image mask maybe based on the thickness of the LV as measured on the CT image.Exemplary image mask thicknesses for the chambers may then be estimatedbased on the LV measurement, for example: 0.3 to 0.5×LV thickness forthe image masks of the LV, right ventricle (RV), right atrium (RA) andleft atrium (LA). Or, for example, the multiplication factor may be,0.3, 0.7, 1.2, 1.5, 2.0, or other smaller, intermediate or largervalues. The zone for searching for GPs may be a function of LV thicknessaway from the wall, and/or in mm.

Different walls make have different masks. The image mask may bepositioned to contain the GPs and/or surrounding tissue. The image maskmay be centered on the wall, or may be positioned towards one end of thewall. For example, to search for epicardial GPs, the mask may be at theouter edge of the wall. TO search for myocardial GPs, the mask may be atthe middle.

Optionally, the image masks are generated and/or applied based ontemplates. The templates may define: the location of the innervatedorgan (or tissue) and/or the location of the GPs within and/or inproximity to the innervated organ, outside of the organ. The templatesmay be generated, for example based on a predefined anatomical atlasthat maps nerve structures to tissues and/or organs of the body.

Optionally, the generated image masks are adjacent to one another.Alternatively or additionally, the generated image masks overlap witheach other. Alternatively or additionally the generated image masks arespaced apart with respect to one another. The template may define thelocation of the GPs at a distance of greater than about 1 mm, or about 2mm, or about 3 mm, or more from the heart wall.

Optionally, the generated image masks are adjacent to one another. Forexample, to cover a large area in searching for GPs. Alternatively oradditionally, the generated image masks overlap with each other, forexample, to improve matching of GPs to tissue type, and/or whenidentifying GPs in a moving organ such as the heart. Alternatively oradditionally the generated image masks are spaced apart with respect toone another. For example, when searching for GPs in different areas, forexample, to prevent false identifications between the areas.

Optionally, at 4822, the image masks are applied to the functionalimage. Alternatively or additionally, the image masks are applied to thefunctional data. Alternatively or additionally, the image masks areapplied to combined functional and anatomical images and/or data, forexample, overlaid images.

Optionally, the image masks are applied based on the registrationprocess (block 4818). The anatomical information serves as a guide,using the selected image masks, for selective reconstruction of GPrelated data within the functional image. The image masks may becorrelated with the image to contain anatomical structures having theneural tissues. The application may be based on the image registration,for example, applied based on a common coordinate system. The imagemasks may be applied to a certain type of tissue containing neuraltissue. For example, the image masks may be applied to the epicardium ofthe heart. The image mask may be applied to have its inner surfacealigned with the epicardial surface of the chamber wall, such that theimage mask contains the epicardial space encompassing the chamber.

Optionally, the generated image mask is correlated with the functionaldata for guiding the reconstruction of a functional image depicting thetarget nerve tissue.

Optionally, at 4824, functional activity is calculated within theapplied image mask space. Optionally, the average functional activity iscalculated. Optionally, the standard deviation of the functionalactivity is calculated. For the heart example, the functional activityis calculated around each chamber separately, and around the entireheart. Average activity for the chambers may be denoted by A1LV, A1RV,A1LA, A1RA. Average activity for the heart may be denoted by A1H.Standard deviation of the activity may be denoted by SD1LV, SD1RV,SD1LA, SD1RA, SD1H. Optionally, average activity and/or standarddeviation may be calculated for the entire functional image or data.Optionally, average activity and/or standard deviation may be pre-set,e.g., based on previous imaging of the same patient, based on “normal”patient activity etc.

Optionally, at 4826, one or more of 4820, 4822 and/or 4824 are repeated.Alternatively, one or more of 4820, 4822, 4824, 4828, 4830, 4832, 4834,4836 and/or 4838 are repeated. Alternatively, one or more of all blocksin FIG. 2B are repeated. Optionally, additional image masks aregenerated for different anatomical parts (e.g., for different heartchambers, for different tissue layers), optionally for different tissuestypes containing neural tissue. Optionally, additional image masks aregenerated for anatomical tissues and/or anatomical parts that are nearbyand/or adjacent to the earlier analyzed anatomical parts. Differentimage masks may be generated, and then applied together to identify theGPs innervating the organ. For example, different types of GPs mayinnervate different tissues. Alternatively, different image masks areprocessed separately, for example, to differentiate between differentGPs (e.g., located within different tissues of the organ).

Alternatively or additionally, image masks are generated for differenttime frames, optionally on each image of the dynamic cycle (e.g.,cardiac cycle). The mask may be dynamic. The mask may change over timeafter temporal registration. Optionally, the mask is a spatiotemporalmask. The dynamic image masks may correlate with the anatomical regionsof interest during the cycle. For example, the image masks may move withthe heart during the cardiac cycle, but maintaining the same relativeposition. For example, image masks applied to the LV wall move back andforth (and/or become smaller and larger) as the heart contracts andrelaxes, but maintain the relative position against the LV wall.

Alternatively or additionally, image masks are generated for both theanatomical and the functional images. For example, image masks aregenerated based on the combined and/or registered images, which may forma single image, or two separate (optionally linked images).

Optionally, the anatomical images are obtained during a cyclicphysiological process (e.g., cardiac cycle, bladder emptying, intestinalperistalsis). Optionally, different spatiotemporal image masks areselected for different images obtained during the physiological process.Optionally, the different spatiotemporal image masks are synchronizedwith the physiological process to correspond to the same location of thetissues. In this manner, the location of the tissues may be maintainedas the tissues move during the physiological process.

For example, at 4820 (repeated) additional image masks are generated todetect neural tissue within the myocardium. The size and/or shape of themyocardial masks may be different than the size and/or shape of theepicardial masks and may correspond to different regions within theheart. For example, epicardial image masks may be aligned with theepicardial surface of the chamber wall, such that it will contain theepicadial space encompassing the chamber. The myocardial image masks mayencompass the walls of each chamber.

Exemplary myocardial image mask thicknesses include: 1.2×LV thicknessfor the image masks of the LV, 0.7×LV thickness for the RV, 0.4×LVthickness for the RA, 0.4×LV thickness for the LA, or othermultiplication factors (for each thickness) for example, 0.4, 0.7, 1.0,1.2, 1.5, or other smaller, intermediate or larger values.

In another example, neural structures are identified within the septum.Image masks may be created for the septum.

For example, at 4822 (repeated) the image masks are applied to the imageto correlate and/or contain myocardium.

For example, at 4824 (repeated) the average and/or standard deviation ofthe functional activity may be calculated for the myocardium imagemasks. Average activity for the chambers may be denoted by A2LV, A2RV,A2LA, A2RA. Average activity for the heart may be denoted by A2H.Standard deviation of the activity may be denoted by SD2LV, SD2RV,SD2LA, SD2RA, SD2H.

Optionally, the calculated activity levels are normalized, for example,to a point or volume in the body, to a point or volume within the imagemask space, or other methods. The normalization may allow foridentification of the GPs for example, within the mediastinum.

Optionally, at 4828, GPs are identified within the applied image maskspace. It should be noted that ‘GP’ term is used for ease of discussionand that the method may be applied for identifying ANS component(s) orfor extracting or identifying other information relating to neuralactivities, or other tissues. Alternatively or additionally, GPs areidentified within the organ volume and/or nearby tissues. Optionally,GPs identified within multiple different image masks that are combinedinto a single image of all the identified GPs, for example, theidentified GPs within the organ. Alternatively or additionally, GPsidentified within corresponding image masks of multiple frames (e.g.,all image masks of the LV myocardium during the cardiac cycle) over timeare combined.

Optionally, the GPs are identified by adjusting the position and/or sizeand/or shape of the image mask. Optionally, the image mask is adjustedbased on the corresponding anatomical image. Optionally, the image maskis adjusted to exclude regions that may not physically contain GPs.Optionally, the functional data is adjusted instead of, and/or inaddition to, and/or based on the adjusted image mask. For example,functional intensity data obtained from anatomical regions which may notinclude nerve structures, for example, inside the hollow (e.g., fluidfilled) space, such as heart chambers and/or blood vessels. The chamberitself may not contain nerves. When intensity readings are detected inthe chamber (e.g., next to the heart wall), the image data and/or imagemask may be adjusted to reflect the estimated position of the intensityreadings. Mask adjustment may be required, for example, whenregistration between anatomical image data and functional image data isimprecise and/or incomplete. For example, the anatomical image data andfunctional image data were obtained at different angles.

Optionally, the GPs within the image mask and/or organ volume arelocated. The relative position of one GP to another may be calculated,for example, in 2D and/or 3D.

Optionally, the GPs are combined together into an ANS map or ANS data.Optionally, connectivity between GPs is determined Connected GPs may bewithin the same image mask, within different images masks at differentspatial locations, and/or within different image masks at differentpoints in time (but at the same corresponding location). Optionally, thespatial relation between GPs is determined. For example, the relativelocation between a first GP with respect to the location of a second GP.

Optionally, areas of extreme activity are identified. For example,epicardial GPs (EGP) and/or myocardial GPs (MGP) are identified based onextreme mIBG activity.

Optionally, GPs are identified based on one or more predefinedthresholds and/or rules. Optionally, GPs are identified based on size.Alternatively or additionally, GPs are identified based on activitylevel in reference to average activity and/or surrounding activity.Alternatively or additionally, GPs are identified based on connectivitybetween GPs.

Optionally, the GP may be identified as an object with a size of atleast about 4×4×4 millimeters (mm) (e.g., for an EGP), or about 2×2×2 mm(e.g., for an MGP). Alternatively or additionally, the GP may beidentified by comparing calculated activity (e.g., image intensity) of acertain region to surrounding activity in the same image mask.Alternatively or additionally, the GP may be identified by comparingcalculated activity (e.g., image intensity) within the image mask toactivity in another image mask. For example, the EGP may be identifiedas satisfying the rule that the total activity of the EGP is apredefined factor times the standard deviation (SD1 and/or SD2), aboveaverage activity (A1 and/or A2), and/or the adjacent activitysurrounding it is lower than half of the EGP activity (e.g., correlatedfor volume). Optionally, the user may select and/or modify thepredefined factor. For example, the MGP may be identified as satisfyingthe rule that the total activity of the MGP is another predefined factortimes the standard deviation (SD1 and/or SD2), above average activity(A1 and/or A2), and/or the adjacent activity surrounding it is lowerthan half of the MGP activity (e.g., correlated for volume). Optionally,the user may select and/or modify the predefined factor.

Optionally, identification of GPs is performed per frame, optionally perframe of the dynamic cycle (e.g., cardiac cycle).

Optionally, the identified GP is automatically related to a tissue type.Optionally, the identified GP is related to the tissue type based on theapplied image mask. Alternatively or additionally, the identified GP isrelated to the tissue type based on the characteristics of the intensityreadings, for example, large sizes (denoting large GPs) may only befound in certain tissues. Optionally, different types of GPs are relatedto different tissues. For example, myocardial GPs are related to themyocardium and/or epicardial GPs are related to the epicardium.

Optionally, at 4830, one or more parameters are calculated for theidentified GPs (also referred to herein as GP parameters). Examples ofparameters include: average size, specific activity (e.g., counts pervoxel of GP/average counts in the corresponding image mask volume),power spectra (e.g., power below 1 Hz, power between 1-5 Hz, ratio ofhigh to low frequencies), normalized power spectra, GP connectivity map(e.g., connectivity and interaction between different GPs), number ofGPs per predefined area (e.g., GP density number/square centimeter).

For example, for identified EGP, one or more of following parameters maybe calculated: EGP size, EGP specific activity, EPG power spectra graph,EGP normalized power spectra (i.e., the difference between the EGP powerat different frequencies minus the power of the total counts from themyocardial image mask space), EGP connectivity map.

For example, for identified MGP, one or more of the following parametersmay be calculated: MGP number in an area and average size for eachpredefined area (Marshal ligament, left inferior LA wall, right inferiorLA wall, other areas), MGP specific activity, MGP power spectra, MGPnormalized power spectra (i.e., the difference between the MGP power atdifferent frequencies minus the power of the total counts from themyocardial image mask space).

Optionally, calculation of GP parameters is performed per frame,optionally per frame of the dynamic cycle (e.g., cardiac cycle).

Optionally, at 4832, the calculated and/or other parameters may benormalized. Normalization may take place at one or more blocks of themethod, for example, during and/or after acquiring the functional and/oranatomical images, upon calculation of functional activity, uponidentification of GPs, upon calculating parameters for the GP, uponcomparison of data over time, or at other blocks.

Examples of one or more normalization techniques include: raw data, rawdata divided by the raw data value in a known fixed anatomical locationacquired at roughly the same time (for example, the activity of thetracer in the patient's mediastinum), normalization to a normal patientdata set, normalization to a value of the activity at the first or thelast image acquisition from a sequence of acquisitions, normalization tovalue acquired at different physiological state (e.g., rest, stress), acombination of some or all of the above, and/or other methods.

Alternatively, the normalization of 4832 is performed instead of and/orin addition to, before a different block in the process, for example,before GPs are identified in block 4828. The normalization may help inidentifying the GPs. For example, activity level (e.g., mIBG level) at alocal region is compared to an average value and/or standard deviationacross the organ volume, within the image mask space and/or relative toa predefined threshold.

Alternatively or additionally, the calculated data (e.g., blocks 4824,4828, 4830) and/or measured functional intensity are corrected forsensitivity. Optionally, sensitivity correction is performed within eachimage mask and/or in related image masks. For example, some areas mayhave relatively higher sensitivity to uptake of the radioagent, and somemay have relatively lower sensitivity to the uptake of the radioagent.Optionally, the anatomical data is correlated to the sensitivity.Optionally, the image masks are generated (block 4820) based ondifferent sensitivity levels, for example, one set of image masks forhigher sensitivity nerve structures, and another set of image masks forlower sensitivity nerve structures. Optionally, the differentsensitivities are normalized to a common baseline.

Alternatively or additionally, measurements of the functional data arenormalized, for example, measurements of uptake of the radioagent arenormalized to the level of corresponding chemical in the patient.Optionally, intensity measurements are normalized according to the levelof activity of GP being identified. Optionally, measurements denotingactivity of the GPs are taken. For example, in the case of mIBG,measurements may be normalized to the level of norepinephrine (NE)(and/or adrenaline and/or epinephrine) in the patient. For example, thelevel of NE is measured in the blood (e.g., by blood sample), urine, orother body fluids. The intensity of mIBG uptaken is normalized based onthe measured NE. Additionally or alternatively, mIBG measurements may benormalized to a decay function of mIBG over time (e.g., from theinjection of the mIBG). In another example, the level of activity ismeasured by non-chemical methods. For example, normalization of mIBG isperformed based on measurements taken during a cardiac stress test(e.g., based on ECG measurements, heart rate, cardiac output, or othermeasurements). The measurements may be correlated with levels ofactivity of the GPs being identified (e.g., by a table, mathematicalequation, or other methods).

Optionally, at 4834, data is compared over time. Optionally, changes inGP parameters over time are identified. Optionally, dynamic changes ofthe calculated parameters between different acquisition times aredetermined. For example, the changes in GP (e.g., EGP) activity overtime may be calculated, from injection till 6 hours post injection, byrepeating the image acquisition several times during this time window.The functional images may be acquired at more than one time after thetracer injection.

Optionally, at 4836, a functional image is reconstructed based on themask applied to the functional data and/or image. Alternatively oradditionally, an image is reconstructed based on the mask applied to thecombined functional and anatomical data and/or images. The reconstructedimage may contain the identified GPs, for example, as regions ofincreased intensity. The reconstructed image may be overlaid on theanatomical image, illustrating the physical location of the GPs.

Alternatively or additionally, the characteristics of the GPs within thefunctional image are reconstructed. The reconstruction is instructed bythe image mask.

Optionally, at 4838, the calculated results (e.g., block 4828, 4830,4832, 4834) and/or reconstructed images (block 4836) are provided forpresentation or otherwise provided to the operator. For example,presented on a monitor to a physician. Additionally or alternatively,the calculated results and/or reconstructed images may be stored in amemory for future use (e.g., diagnosis). The calculated results may helpin diagnosing the patient (e.g., as described with reference to block216) and/or in guiding treatment (e.g., as described with reference toblock 228).

Optionally, the results are provided for presentation on a certainframe, for example, the end systolic frame. Alternatively, results areprovided for presentation on multiple frames, for example, a video ofthe cardiac cycle.

Optionally, the reconstructed functional image or combined functionaland anatomical image is provided for registration during a treatmentprocedure. The reconstructed functional image may be overlaid on and/orregistered with anatomical images obtained during the treatmentprocedure. The overlaid and/or registered images may be used by theoperator to physically determine locations of the GPs during thetreatment.

The method of FIG. 2B has been described with reference to the heart.The method is not limited to the heart, and may be used for otherorgans, hollow fluid filled organs (e.g., stomach, aorta, bladder)and/or solid organs (e.g., kidney, liver). GPs and/or nerve endings maybe identified in the other organs. For example, the aorta may besegmented based on surrounding structure (bones, muscles, branchingarteries) and image masks generated accordingly. For example, the livermay be segmented based on anatomical liver lobe divisions.

Referring now back to FIG. 2A, alternatively or additionally, theganglions are located according to one or more mapping functions whichmap a reference kinetic behavior and/or an uptake rate for one or moreregions of the imaged intrabody volume.

For example, the registration may be performed by a correlation matrixwhich may be calculated in advance to the specific intrabody volumeimaged in the functional data and the anatomical data. In someembodiments, the nervous tissue may be located by identifying one ormore unique properties of uptake and/or kinetic information and/orrelationship to an uptake and/or kinetic information of surroundingtissues and/or organs. For example, a layered image is formed wherefunctional data is added as an additional layer on top of an anatomicalimage, such as a fluoroscopy image, optionally forming the ANS map. Thecombination may be performed by presenting the functional dataside-by-side with, registered with and/or overlaid on the anatomicaldata.

It should be noted that combining the anatomical data and the functionaldata may increase the SNR of the functional data. Registering thefunctional data and the anatomical data (e.g., to a single coordinatesystem) may indicate an anatomical region in which different uptakeindications may be shown. This may allow filtering the functional dataaccording to an estimated volume in the anatomical data in which atarget nervous tissue is located (for example, by using image masks asdiscussed with reference to FIG. 2B).

Optionally, the localization and/or imaging and/or identification maybegin before and/or simultaneously with the injection of the imagingagent. In another example, the imaging starts immediately after theinjection of the imaging agent. In an example, the imaging starts afterthe injection at a delay of about up to 5 minutes, about 10 minutes,about 30 minutes, about 1 hour, between about 1 and about 10 minutes,between about 5 and about 20 minutes, between about 10 and about 30minutes, between about 15 and about 60 minutes, between about 30 andabout 120 minutes, between about 1 and about 6 hours, or between about 5and about 48 hours.

Optionally, more than 2 imaging steps may be provided for localization.Optionally, the localization includes acquisition of dynamicphysiological processes, such as dynamic perfusion, dynamic traceruptake, dynamic tracer washout, and the like.

Optionally, at 214, an ANS model for ganglion connectivity is generated,for example, by an ANS generation module 502D. The model may begenerated based on the identified and/or located ganglions (block 212),for example, based on ANS map or data. Optionally, the ANS model is theANS map or ANS data. The model may be generated, for example, asdescribed herein. The model may be generated by linking betweenidentified ganglions. Optionally, the model links between spatiallylocated GPs.

Alternatively or additionally, a map is generated.

The map and/or reconstructed images may contain, for example, GPs, nerveending density in tissue, tissue functionality, tissue anatomy, tissuesurrounding the nerves (e.g., fat pads), anatomical data, other datasuch as electrical activity, MRI based functionality, CT based physicaldata, and/or other data.

The image may be, for example, 2D, 3D, 3D with anatomical registrationlandmarks, image patches, nuclear medicine data, and/or other data.

The generated map may be displayed, may be used for navigation fortreatment, may be further analyzed, and/or may be transferred (e.g.,using physical media and/or downloaded).

Optionally, the ANS model may comprise of one or more reconstructedimages (for example as discussed in reference to 4836). In someexamples, the reconstructed image is of a certain tissue region, or avolume or a selected region of interest. In some examples, thereconstruction is based on voxels, segments, or model based or acombination thereof. In some examples, the image reconstruction mayprovide intensity of uptake of the one or more radiotracers, or thekinetic parameters that correspond to the dynamic behavior of theimaging agent in the innervated tissue, nerve tissue and/or in the bloodvessels.

Optionally, at 216, a diagnosis is performed and/or assigned to thepatient. Optionally, the diagnosis includes the underlying neuralanatomical structures believed to be contributing and/or causing thepatient's symptoms and/or disease. Alternatively or additionally,contribution by neural tissue to the patient's condition is ruled out,for example, the imaging analysis may indicate normal neural tissue. Thediagnosis may be made manually by the physicians and/or automatically bysoftware. For example, software may compare between the generateddistribution of the imaged tissue with one or more sets of expecteddistributions (e.g., of ‘normal’ patients and/or previous distributionof the same patient). Abnormal activity may be detected based on thecomparison.

Optionally, at 218, the generated ANS model (block 214) is stored, forexample, on data repository 512. Optionally, the diagnosis (block 216)is stored. Other data may also be stored, for example, the functionaland/or anatomical raw images.

Optionally, at 220, therapy is selected for treating the patient.Optionally, the therapy is selected based on the diagnosis (block 216).

Optionally, localization of ANS component(s) based on the combination ofthe functional data and the anatomical data may be used for selectingand/or guiding a medical treatment (the instrument guidance may be basedon the localization), for example a denervation procedure, such as renaldenervation or denervation of ganglia in the atria, a muscle ablationprocedure (for example of the atrial and/or ventricular walls),innervations modulation procedure, blood treatment and/or stentplacement procedure (in a blood vessel), for example as describedherein. For example, the localization may be used for guiding anablation of ganglia in the atria, for example as a procedure of treatingatrial fibrillation (AF), for instance during a catheterizationprocedure, optionally based on a combination of SPECT data and theanatomical data. Optionally, the guided catheter is an intracardiacechocardiography (ICE) catheter. In such embodiments, the imaging datafrom the ICE catheter may include anatomical data that may be combinedwith the SPECT data or image and/or reconstructed image.

Optionally, an estimated prediction of success of an ablation procedureis given, for example, based on the measured uptake where for example anestimation of a failure may indicate a recurrence of an arrhythmia and asuccessful estimation means an arrhythmia reduction and/or elimination.In such embodiments, there may be a value to the location(s) in whichuptake rate is measured. For example, the ROI may be in the leftventricular (LV) and/or in the atria. Optionally, ROIs are obtained byusing image masks. It should be noted that for mIBG, the overall atriauptake is far less than in the uptake in the LV. For example, GPs incertain locations may denote a relatively high ablation success rate,whereas GPs in other locations may denote a relatively low ablationsuccess rate. Other examples include prediction based on the map of GPs(ANS map), for example, the success rate for ablation of highlyinterconnected GPs may be lower than ablation of low interconnected GPs.Optionally, an estimation module automatically calculates the estimatedprediction of success.

Optionally, at 222, the ANS model and/or map (e.g., surface of datalinked to anatomical landmarks, such as 2D and/or 3D) and/or diagnosisis loaded to a catheter navigation system (e.g., navigation system 314).Optionally, the navigation system is a 3D electrophysiological (EP)system. Optionally, the navigation system is designed for GP ablationguidance. Optionally, navigation system 514 is the CARTO® system.Optionally, the coordinates of the GPs and/or maps of inter-GP links areloaded into the CARTO® system for displaying the location of the GPsand/or map relative to the treatment catheter of the CARTO® system.

Optionally, the model is sent to a server to be merged with thenavigation system (e.g., CARTO® system). Optionally, billing isperformed per use, for example, based on a pay per use model.Alternatively or additionally, the model is loaded to portable mediawith the data stored on the media (e.g., memory card, CD), for example,the patient is provided with the model on the CD to take to the nextprovider.

Optionally, billing is automatically performed for the diagnosis and/ortherapy, based on the loaded diagnosis and/or planned treatment. Forexample, the pay per use method, pay per generated map, or othermethods.

Optionally, data is decrypted upon loading to the catheter navigationsystem. The data may be have been encrypted to help ensure patientprivacy. The decrypted data may be displayed, for example, as an image.

The functional data may be acquired before the medical procedure isinitiated, for example few hours and/or a day before the treatmentprocedure (e.g., heart treatment procedure). For example, a SPECT datamay be registered with an electro-anatomical map, for example using aCartoMerge™ module (e.g., by data combining module 502A). Loading theANS model to the catheter navigation system may provide an operator withan accurate guidance during a treatment, such as an ablation procedure.The loading to the catheter navigation system may help the operator planthe treatment before inserting the catheter.

Optionally, at 224, the ANS model is marked-up, for example, manually bya user entering data using input element 518 and/or automatically bysoftware. Optionally, the treatment plan is annotated based on the userentered data and/or automatically generated data. The marking-up and/orthe annotation may help the operator plan the treatment plan beforeinserting the catheter.

Optionally, the maps and/or data is simply overlaid on the CARTO®system, and treated as any other overlay by the system. The physicianmay understand what the overlaid map means.

Optionally, the treating physician marks the points and/or regions forablation, based on the GP image. Optionally, CARTO® (or other systems)understand the data and/or map, and track ablations of the GP.Optionally, the navigation system may track, guide and/or remind theoperator, for example, tracking which GPs were ablated, reminding totest ablation points before and after ablation, automatically markingtreated points, or other functions. Optionally, CARTO® tracks appliedcontract pressure and parameters to indicate how deep into the tissuethe ablation is being applied.

Optionally, the navigation system (e.g., CARTO®) follows current medicalpractice, for example, reminding and/or tracking ablation around thepulmonary vein (PV), in addition to the GPs themselves.

Optionally, CARTO® may track one or more of the described, to estimatethe probability (or provide yes/no) that the operator managed toablation the GP (which is at a distance from the wall or not).Optionally, CARTO® suggests parameters and/or gate ablation to apply toablate the GPs, for example, based on the location of the GP, theablation method, the tissue type, or other factors.

Optionally, CARTO® tracks how deep away from the inner surface of theheart, arteries, and/or other chambers the operator needs to ablate toreach target tissues (e.g., GP).

Optionally, the described CARTO® procedure tracking may be used in othercontexts, for example, for ablation of live tissue in the middle of theventricle wall.

Optionally, electrical data is collected, and the model is marked-upwith the electrical data. For example, electrical mapping of the heart.Electrical data may be collected, and/or the marking up performed usingthe CARTO® system.

Optionally, the treatment is planned based on the reconstructedfunctional image (e.g., method of FIG. 2B) showing the GPs and/or ANSconnectivity map overlaid on the obtained anatomical image.Alternatively or additionally, the treatment is planned based on thereconstructed functional image alone. The overlaying on an anatomicalimage may be performed in real time during treatment, for example,overlaying the functional image over a fluoroscopic image.

Optionally, the system is set-up for ablation of the located GPs. Forexample, the treatment catheter may be selected, the power level for theapplied treatment may be selected and/or set, or other parameters may beselected and/or set.

When SPECT data is forwarded to a workstation that is part of thenavigation system, the workstation may merge a real timeelectro-anatomical map (obtained before and/or during the treatment)with the SPECT data acquired as described above. For example, theworkstation may merge the ANS map (e.g., a CT map with SPECT datashowing ANS component(s)) with the electro-anatomical map to mark-up theANS model. The results may be presented to the operator as an annotationof colored targets on the electro-anatomical map (e.g., on outputelement 516). For example, for heart treatment, image registration ismade by aligning the left ventricle (LV) in images from the differentinformation sources so that the SPECT mIBG spots from a cloud of spotsfalls in the atrial wall (per the segmented anatomical image).

According to some embodiments of the present invention, differentregions of the functional data, for example the SPECT image, areassociated with different organs or tissues, for example with a nervoustissue and surrounding tissues mapped according to one or more mappingfunctions. The mapping functions may be defined in advance, for exampleby a multivariate analysis of SPECT data, for example Dynamic SPECT dataand angiographic data. The map may allow differentiating betweendifferent regions of the imaged intrabody volume based on kineticbehavior and/or uptake rate.

For example, FIG. 12 is a flowchart of a method 100 of localizing anervous tissue based on an association of different regions in afunctional (e.g., SPECT) image or data to different organs and/ortissues based on a mapping function, according to some embodiments ofthe present invention. 102′, 103′ are as described above with referenceto block 208 of FIG. 2A. In 311, a mapping function may be provided, forexample from a memory of a computing device (e.g., a mapping module 502Bstored on memory 506). As shown at 312, the mapping function may be usedfor associating one or more regions in the functional (e.g., SPECT)image to one or more organs and/or tissues. As shown at 313, the mappingmay allow localizing a target tissue in relation to surrounding tissues,e.g., for separating a nervous tissue (e.g., ganglia) from a surroundingarea.

Referring back to FIG. 2A. Optionally, at 226, a catheter is insertedinto the body of the patient. The catheter may be inserted through thevascular (e.g., femoral artery access to the heart). A single cathetermay be inserted (e.g., dual functions), or two catheters, for example,one catheter for verifying the treatment points (e.g.,electro-stimulation) and/or one catheter for ablation.

Optionally, the ablation treatment catheter is compatible with theCARTO® system, or is provided with the CARTO® system.

Optionally, at 228, the catheter is navigated to the first treatmentpoint based on the annotations, for example, based on the anatomicalannotations. For example, the operator is presented with a real-timefluoroscopic image overlaid with the ANS map so that the catheter may benavigated in real time to the correct location (e.g., to a specific GP).

Optionally, the catheter is navigated within the patient based on theCARTO® system. Optionally, the catheter is positioned for ablationtowards the GPs displayed using the CARTO® system.

Optionally, the catheter is navigated based on the reconstructedfunctional image pre-overlaid on the anatomical image, for example, theregistered and/or overlaid images have been loaded to the navigationsystem. Alternatively or additionally, the catheter is navigated basedon the reconstructed functional image overlaid on a real-time anatomicalimage (e.g., fluoroscopic image), for example, the reconstructedfunctional image loaded to the navigation system, the navigation systemobtaining the real-time anatomical image. Alternatively or additionally,the catheter is navigated based on the reconstructed functional imagealone, for example, navigation may be based on position sensors.

Optionally, navigation of the catheter is based on position sensors. Theposition sensors may correlate to the reconstructed functional imageand/or ANS map. Alternatively, navigation of the catheter is not basedon position sensors. For example, navigation may be based on visualimage, such as the reconstructed functional image overlaid on areal-time image of the catheter inside the targeted innervated tissues.

Optionally, the catheter is navigated to the located treatment site.Optionally, the localization may be a real time localization which isbased on functional data and/or anatomical data which are capturedsimultaneously or substantially simultaneously and/or during a treatmentperiod, for example during a medical treatment.

Optionally, at 230, the location of the catheter at the treatmentpoint(s) is functionally verified. Functional verification may beperformed manually by the operator and/or automatically by averification module programmed to perform one or more of theverification process. For example, the operator applies the stimulationand the module analyses the results. In another example, the moduleautomatically both applies the stimulation and analyses the results. Inyet another example, the module applies the stimulation and the useranalyses the results.

Optionally, the treatment points are functionally verified by the CARTO®system. For example, the point may be confined by applying highfrequency stimulation to the points and measuring the response.Optionally, the application of high frequency stimulation is to thepoints and their surroundings, e.g., to compensate for any minor errorsin ANS map (e.g., due to noise or registration).

According to some embodiments of the present invention, one or morenervous tissues may be localized by stimulating a nervous tissue in acertain intrabody area and identifying one or more nervous responses inresponse to the stimulation. The stimulation may be pharmacological,mechanical, thermal, and/or electrical, for example, high frequencystimulation (HFS). In such embodiments, after a nervous tissue in anintrabody volume of a patient is stimulated to trigger a nervousresponse which is associated with a certain reference uptake value, afunctional data from a functional modality may be acquired, for exampleas described above. The functional data may be then analyzed to localizethe nervous tissue in the intrabody volume according to the referenceuptake value.

Optionally, the reconstructed image is used to get to a region. Tests onone or more points are performed in the region, for example, todetermine response to HFS, DF, or other testing methods.

Optionally at 232, the identified and/or located treatment point (e.g.,GP) is ablated, for example, using the catheter, for example, with anelectrical, chemical, cryo, and/or other methods of ablation.

Ablation may be irreversible (e.g., necrosis of tissue) or reversible(e.g., using botox).

The ablation may be performed from nearby tissue, for example, frominside the heart chamber to a GP in the heart wall. The ablation may beperformed within the GP itself, or next to the GP, for example, byinserting a needle through the heart wall into the GP itself or nearby.Ablation within the GP itself may spare surrounding tissue.

Optionally, the GPs are ablated using the CARTO® system. For example,energy is delivered and/or controlled using the CARTO® system.

Optionally, GPs are ablated. Optionally, regions containing GPs areablated. Optionally, regions in the heart wall and/or surroundingvasculature are ablated. Optionally, regions in the pulmonary vein areablated.

Optionally, the catheter contains an ablation element, for example, atthe catheter tip. Optionally, the catheter is designed for a force to beapplied to push the ablation element against the target tissue and/orinside target tissue. For example, the ablation element is a needleinserted into the heart wall, or through the wall to reach a fat pad, toinject chemicals such as permanent poisons (e.g., alcohol) or temporary(e.g., botulism toxin) and/or an electrode positioned against the heartwall.

Optionally, the ablation element is positioned and/or directed based onthe location of the identified GPs. Optionally a force is applied (e.g.,automatically by a robot and/or manually by a user). Optionally,ablation energy is applied. The amount of applied force and/or ablationenergy are optionally related and/or measured (e.g, by the catheter tip)to the location of the identified GP that is to be ablated, for example,by a table, a mathematical relationship, or other methods. For example,a GP located 0.5 cm away from the inner surface of the heart chamber maybe ablated by the ablation element located at the surface of the innerheart wall applying certain energy. Another GP located 1 cm, or otherdistances away from the inner wall may be ablated by higher appliedenergy, and/or by applying a stronger force of the ablation element intothe inner wall. In another example, ablation may be performed by highpower ultrasound that is focused by the catheter, changing the focusbased on the depth. Optionally, at 234, the effects of the ablation aremonitored. The effects on the immediate target organ may be monitored.The effects on other organs of the body may be monitored. For example,the effects on the heart and/or the response of the heart to theablation of the GPs may be monitored.

Optionally, monitoring is performed by repeating at least some of theimaging of the ANS. Alternatively or additionally, monitoring isperformed by repeating at least some of the stimulation. The results ofthe stimulating post-ablation may be compared to the effects of thestimulation pre-ablation. The effects of the ablation may be monitoredby the comparison.

Optionally, monitoring is performed clinically and/or using equipment,for example, by clinically observing the patient, by performingmeasurements (e.g., blood pressure, cardiac output, ECG), and/or othermethods.

According to some embodiments of the present invention, functional data(also referred to as SPECT data) may be combined with anatomical datafor an ablation procedure, for example for ablation of a nervous tissuein the vicinity of the atria, for instance as described below. Forexample, reference is now also made to FIG. 4 which is a flow ofclinical protocol for neural modulation of one or more GPs in the atria,according to some embodiments of the invention. First, as describedabove, the patient may be injected with 1-123 labeled mIBG, for examplein a dose of between about 3 mCi and 8 mCi or between about 2 mCi and 12mCi, for example about 5 mCi. The data or the image of the mIBG tracerwith high sensitivity—using high resolution scanner for example D-SPECTmay allow localization in a distinguishable manner the location ofactive GPs, for example in ROIs of the atria. The patient may also beinjected with a supporting radiopharmaceutical, such as Tc-99m labeledtracer for cardiac perfusion mapping, for instance based on a tracersuch as Sestamibi-Tc-99m, Tetrofosmine-Tc-99m, and Teboroxime-Tc-99m.For example, the dose of the Tc-99m labeled tracer is between about 6mCi and 12 mCi, between about 3 mCi and 10 mCi, or between about 2 mCiand 15 mCi, for example about 10 mCi, about 8 mCi and about 5 mCi. Insome examples, the GP localization occurs at rest and/or at stress.

The localization may be done on the uptake of the radiotracer (I-123labeled and Tc-99m labeled) one after the other, for example, firstinject I-123 labeled mIBG, then image, then inject Tc-99m labeled tracerthen image. In another example, the localization may be done on bothradiotracers (I-123 labeled and Tc-99m labeled) simultaneously, thusallowing to obtain fully registered images of the tracers, and inshorter time frame. In some examples, both tracers are injected with thedose ratio of about 2:1 between the Tc-99m labeled tracer and the 1-123labeled tracer. For example, about 10 mCi of Tc-99m (such assestamibi-Tc99m) simultaneously with about 5 mCi of mIBG-I-123. In otherexample, ratio of between about 1:1 to 3:1 is used, or ratio of betweenabout 1.5:1 to 2.5:1 is used.

Optionally, functional imaging (e.g., for the GP localization) and/orthe simultaneous multiple-tracers localization may include photonacquisition over a period of time of about 10 minutes, about 5 minutes,about 3 minutes, about up to 2 minutes, about 8 minutes, about 2 to 8minutes, about up to 10 minutes, about up to 15 minutes, and/or about upto 20 minutes.

Optionally, at 236, the effects of the treatment matching the ANS modelis confirmed. Treatment may continue upon confirmation, or end if allpoints have been treated and/or the desired effect (full or partial) hasbeen achieved. Alternatively, the effects do not match the ANS model, inwhich case, for example, the operator may decide to stop treatment orre-evaluate the next treatment point.

Optionally, the effects of ablation treatment are confirmed using theCARTO® system. Optionally, HFS is applied to the treatment area by theCARTO® system. A negative response may indicate successful ablation ofthe GP.

Optionally, the effects are determined based on repeating at least someof the imaging of the ANS. Alternatively or additionally, the effectsare determined based on repeating at least some of the stimulation. Theresults of the imaging and/or stimulating post-ablation may be comparedto the imaging and/or effects of the stimulation pre-ablation. Theeffects of the ablation may be monitored by the comparison.

Optionally, at 238, additional locations are ablated based on thetreatment plan and/or based on the monitored effects. Alternatively,treatment is continued at the same point.

Optionally, some of the blocks of the method are repeated, optionally,the catheter is moved or rotated to another location (228) or remains inthe same location; the point is verified (230) or the same point ismaintained; the point is ablated (232), the effects are monitored (234)and/or the effects are confirmed (236).

Optionally, at 240, progression is monitored after the treatment sessionhas been completed. The patient may be monitored on an outpatient basis,for example, by clinical examination, blood tests, ECG, or othermethods. The patient may be monitored by repeated functional and/oranatomical image. The patient may be brought in for one or moreadditional treatment sessions.

Optionally, the localization may be used for monitoring the nervoustissue, for example in a plurality of sessions held during a treatmentperiod, for example: during a treatment period of a day, a week, amonth, a year or any intermediate or shorter period.

The methods and/or systems described herein refer to identificationand/or treatment of nerve structures in the body of a patient. Themethods and/or systems may be used for ablation of other structures inthe body. The other structures may not been visible (e.g., too small,resolution not high enough, similar to surrounding tissue) usinganatomical imaging modalities, for example, lymph nodes, cancermetastases, or other structures. For example, to detect metastaticthyroid cancer, TSH-stimulated low-dose 131I whole-body scanning withserum thyroglobulin either by standard LT4 withdrawal or rhTSHstimulation may be used. For example, to detect bone metastases, 99m Tcmethylene diphosphonate (MDP) may be used. For example, to image lymphnodes, 18F-FDG may be used. Optionally, the systems and/or methods maybe used for identification of objects with an expected size and/or shapeand/or activity located within a window relative to anatomical landmarksthat may be mapped using the functional modality and/or anatomicalmodality that may be registered to another image, such as a nuclearmedicine image. It is noted that combined CT and nuclear medicineimaging may be performed to obtain anatomic registration, and then applythe method described with reference to FIG. 2B.

One or more of the blocks of method 200 of FIG. 2A are now discussed inadditional detail.

With reference to block 212, optionally, as depicted in FIG. 4, thelocalization may occur in a number of sessions, for example to providean early image and a late image (repeating blocks 206, 208 and/or 210).For example, a first localization step of about 10 minutes is followedby a wait period which is further followed by a second imaging step ofabout 10 minutes. In some examples, the wait period between imagingsteps is of about 5, about 10, about 20, about 30, about 45, about 60,about 90, and about 120 minutes or any intermediate or longer periods.For example, the wait period is between about 5 and about 30 minutes,between about 20 and about 60 minutes, between about 30 and about 120minutes, between about 1 and about 5 hours, or between about 2 and about48 hours.

With reference to block 228, the operator may navigate a catheter intothe heart for treatment. For example, reference is now made to FIG. 5,which is a schematic illustration of a human heart 300 and a set of fourganglionic plexi (GPs) 301-304 and their axons respectively in thesuperior left GP (SLGP), inferior left GP (ILGP), anterior right GP(ARGP), and inferior right GP (IRGP) of the human heart 300. The imagealso depicts a coronary sinus 306, which is enveloped by muscular fibersthat have connections to the atria, and the vein and ligament ofMarshall 305, which travels from the coronary sinus to the regionbetween the left superior pulmonary vein (LSPV) and the left trialappendage (LAA) and includes the Marshall GP. The GPs are located in fatpads. One GP is located at the right pulmonary vein (RPV) fat padlocated at the junction of the right atrium and right pulmonary veinsand provides a direct vagal inhibition of the Sinoatrial (SA) node.Another GP is located in the inferior vena cava and inferior left atrium(IVC-ILA) fat pad, at the junction of the IVC and ILA, selectivelyinnervates the Atrio Ventricular (AV) nodal region and regulates AVconduction. Another GP is located in the SVC-AO fat pad, between themedial superior vena cava (SVC) and aortic root superior to the rightpulmonary artery, a “head station” of vagal fibers projecting to bothatria and to the IVC-ILA and PV fat pads.

One or more of the heart neural structures may be displayed for theoperator for navigation and/or treatment. The combination between thefunctional data and the anatomical data may allow guiding the ablationprocess (e.g., by creating ANS map or data), for example by indicatingto the operators where the GPs are located (block 224), allowing theoperator to ablate some or all of them by operating the ablation unit asdescribed above (block 232). The ablation unit is optionally used forhigh-frequency stimulation when guided to proximity with some or all ofthe above GPs and/or another ganglia area. Optionally, pre acquiredsegmented images are used, for example anatomical imaging data from amodel indicating the location of some or all of the above GPs, forexample imported via an image integration module, such as CartoMerge™module (block 222). Optionally, data pertaining to the treated GP isacquired and used for the imaging and/or the guiding of the treatmentprocess, for example spatial distribution and/or thickness of theepicardial fat in the surrounding area, for example of the fat padwherein the GP is located. For example, ablation of GP may be an optionfor treatment of patients with paroxysmal or persistent AtrialFibrillation (block 220).

Referring to block 210, optionally, the functional data is segmentedbefore the combination thereof with the anatomical data. For example,pulmonary vein (PV) sections, left atrium (LA) sections, and/or GPs aresegmented, for example based on a match with a model.

Reference is now made to FIG. 6, which is a flowchart of another method800 for performing an ablation treatment by mapping complex fractionatedatrial electrograms (CFAE) sites, contractile force (CF) sites, and/ordominant frequency (DF) sites in the atria as target areas, according tosome embodiments of the present invention. The method of FIG. 2A may bemodified according to the method of FIG. 6. First, as shown at 801,CFAE, CF, and DF sites may be mapped, for example, an ANS model may begenerated (block 214), and/or the sites may be displayed on the model(block 224). Then, as shown at 802, intersections between the CFAE, CF,and DF and/or CFAE, CF, and DF and GPs may be calculated. Theintersections may be with anticipated sites of anatomically known GPs,for example the above described GPs, with pre-acquired localized GPs,for example GPs which are identified in the SPECT data, and/orintersections with GPs located in real time by high-frequencystimulation. Then, as shown at 803, the intersections may be selected astarget areas for ablation (e.g., block 224).

For example, reference is now made to FIGS. 7A-7D, FIGS. 8A-8D, FIGS.9A-9D, FIGS. 10A-10D and FIGS. 11A-11D. Each set of figures having acommon numeral includes CFAE, CF, and/or DF sites and/or intersectionsof CFAE, CF, and/or DF sites in four views (clockwise): right anterioroblique (RAO). Posterior-anterior (PA) view, a right lateral view (leftside) and a posterior view (right side), which may be identified, forexample, using the method described in FIG. 6, according to someembodiments of the present invention. FIGS. 7A-7D depict a mapping ofCFAE areas 707. FIGS. 8A-8D depict a mapping of CFAE areas 909 and theintersections thereof with ARGP 911, SLGP 912, ILBP 913, and IRGP 914.FIGS. 9A9-9D depict a mapping of CFAE areas 909 and intersectionsthereof with both ARGP 911, SLGP 912, ILBP 913, and IRGP 914 and with DFsites, for example site 920. FIGS. 10A-10D depicts a mapping of CFAEareas 909 and intersections thereof with CF sites 921. Optionally, anintersection between a CFAE area, a DF site, and a GP is identified as atarget location for ablation, for example see the full dots depicted inFIGS. 11A-11D which are RAO, PA, a right lateral, and a posterior views,for example the full dot 950. Optionally, a full intersection ispreferred over a partial intersection.

In addition to, or instead of GP detecting per se, the nervous tissue istypically composed of neurons, axons and synapses and typically containsa high fat composition and/or located within and/or in proximity to fattissue. As a result, structural imaging of nervous tissue ischallenging, at least. Methods for detecting or locating ganglions ofthe nervous tissue are described above. In some exemplary embodiments ofthe invention, such methods are extended and/or supplemented to detectsynapses and/or other nervous tissue which innervates a target tissuesuch as the heart, GI tract, or other tissues and/or end organs asdescribed herein.

In some embodiments of the invention, a functional imager (e.g., SPECTor PET) may use a tissue specific tracer (mIBG for example or anothertracer) with affinity to one of the functions related to the autonomicnervous system (e.g., Nor Epinephrine production, secretion orprocessing, Acetylcholine production, secretion or processing and/orDopamine production secretion or processing). Additional details ofsuitable tracers may be found, for example, with reference to PCTapplication titled “NERVE IMAGING AND TREATMENT” (Attorney Docket No.58463), co-filed with the present application.

In some embodiments of the invention, the specific tracer is selectivelytaken up by the target nervous tissue and functional information may beacquired (e.g., as radiation counts). In some cases, the acquisition istimed to a stimulation or other modulation of the nervous system, forexample, drug provision, electrical stimulation, mechanicalstimulations, body interaction (e.g., cold water on hand or face) and/orexercise, so that the acquired data can reflect not only a steady stateof the body but also, or instead, reaction to a stimulus.

Various methods are known in the art to inject these tracers to receiveimages of intra body uptake thereof. However, the signal to noise ofthese tracers, coupled to the low resolution and sensitivity of theimaging machines was considered (to the extent the possibility wasraised, which is not clear) a barrier to identify and localize smalltargets, for example, tissue denervation and/or ganglions. In someexemplary embodiments of the invention, for example, as describedherein, nervous tissues with a maximal extent smaller than, for example,20 mm, 10 mm, 5 mm, 3 mm and/or 2 mm are identified. Optionally oralternatively, innervated tissue is identified, for example, withsurface sizes of less than, for example, 10 cm sq, 5 cm sq, 4 cm sq orsmaller.

In some exemplary embodiments of the invention, activity of theautonomic nervous system (ANS) is identified and/or localized, forexample, with a resolution good enough to identify ganglions (e.g., <10mm, <5 mm) and/or synapses, for example, the distribution ofintra-tissue synapses of the ANS.

In some exemplary embodiments of the invention, the functional data maybe segmented using an anatomical model (e.g., structural or anatomicalimager—for example: an X-ray CT image). In some embodiments of theinvention, a reconstruction of the functional data is performed usingthe structural model provided by the structural imager (e.g., CT). Insome embodiments of the invention, functional data is assigned to tissueaccording to the segmentation. In some embodiments of the invention,activity tissue within the organ is analyzed according to an assumptionre innervation. For example, processing is optimized for sensitivity, atthe expense of resolution. Tissue outside the organ is optionallyprocessed with an emphasis on resolution, for example, to detect objectsof a size, shape and/or location which match anatomical expectations ofganglions. In some embodiments of the invention, the locations arerelative to anatomical landmarks on the organ and/or as a function ofdistance from the organ boundary.

In some examples of a heart, anatomical data, such as from a CT imagermay be combined with functional data (e.g., mIBG data and/or data fromcardiac tracers) and various algorithms (e.g., for example algorithmsdescribed in U.S. Pat. No. 8,000,773 and related applications) may beused to detect the boundaries of the myocardium of the 4 chambers and/orrelated structures of the heart. Then the registration of the differentimages from the different modalities may be performed and used todistinguish the relevant mIBG activity within the corresponding volumeof the myocardium.

In some embodiments of the invention, ANS component(s) (e.g., ganglions)are identified or detected or localized using methods as describedabove, for example, using the method of FIG. 2B. Optionally oralternatively, the following method may be used. The general (e.g.,average) activity of mIBG may be measured in a region (reapplied withvarious sizes) and compared to a threshold which may be a function ofvariation of the mIBG activity in the region (e.g., 2, 3, 4, orintermediate standard deviations of the regional activity). Optionallyor alternatively, bodies of the size of, for example, 1, 2, 3, 4, 5, 6,7, 8, 9 mm or more or intermediate sizes that appear in multiple (e.g.,2, 3, or more runs (e.g., with various region sizes and/or locations)may be identified as ganglia. In some embodiments of the invention, atleast two finds of a same body location in a region of size that islarger in volume by a factor of at least 2, 4, 6, 8, 10, 20 orintermediate amounts, than the found suspected ganglion, are required.

In some embodiments of the invention, sympathetic and parasympatheticganglia and synapses may be distinguished by stimulating with a stimuluswhich affects only one and detecting which ganglia and/or synapses areaffected. For example, such stimulation may be provided simultaneouslywith injection of a tracer and uptake of the tracer compared to standardspeed.

In some embodiments of the invention, afferent and efferent nerveconduits may be distinguished by selectively stimulating at one pointand comparing effects upstream and/or downstream and/or determining theorder of activation or other effect at two points along the conduit. Forexample, in efferent conduits, activity is expected to show first and/ormore strongly in ganglions. Blocking the ganglions, for example, using asuitable electrical and/or pharmaceutical stimuli may prevent and/orreduce synapse activity. In parasympathetic nervous tissue the oppositeeffects are expected.

FIGS. 13-15 show the distribution of the sympathetic synapses on theheart as imaged on a human patient, whose heart was segmented usingx-ray CT images, in accordance with exemplary embodiments of theinvention.

In general, in these images, the colors are calibrated according torelative mIBG activity, with red being high activity and green being lowactivity. Ganglia are not shown in these images.

FIG. 13 shows an image of the left atrium 1304 and left ventricle 1302,in which the left atrium is colored in accordance with mIBG activityaccording to an exemplary embodiment of the invention, showing a maximalactivity level in the left inferior pulmonary vein 1306;

FIG. 14 shows an image of the right ventricle 1704 and left ventricle1302, in which the right ventricle is colored in accordance with mIBGactivity according to an exemplary embodiment of the invention, showinga maximal activity level in the intra ventricular septum 1706, which isan intra-septal hot spot. Ablation at 1706 may treat Hypertrophiccardiomyopathy (HCM) and/or hypertrophic obstructive cardiomyopathy(HOCM); and

FIG. 15 shows an image of the left atrium 1304 colored 1906 inaccordance with mIBG activity, according to an exemplary embodiment ofthe invention. Of particular interest is a hot spot of activity near theinter-ventricular speta, which has apparently not been known in the artand not used for planning treatment and/or diagnosis. In some embodimentof the invention, the resolution of the areas of activation is between 1and 10 mm in linear resolution (e.g. 3 mm, 5 mm, 7 mm or intermediateresolutions), for separating between locations in different decades ofpercentiles in a histogram of mIBG activity, as measured by counts.

It is also noted that while there may be some correlation between fatpad location and synapse locations and this may be used to guide imagereconstruction, for example, to preferentially assign mIBG counts tothose regions, the fat pads do not necessarily indicate the exactpattern of densities of synapses.

Reference is now made to a set imaging sessions and ablations performedto image and to treat target areas, cardiac sites with ganglionicplexuses, according to some embodiments of the present invention.

The target areas have been identified according to the above methods,for example according the method of localizing nervous tissue based on acombination of anatomical data and functional data—e.g., SPECT data, ofan intrabody volume depicted in FIG. 2 and/or using the system depictedin FIG. 3. In some embodiments of the invention, the following proceduremay be used: a CT anatomical image of the heart and its surroundings andan mIBG nuclear medicine (NM) image of the heart and its surrounding maybe acquired. Optionally, the shape of the heart identified in the CTimage is used for reconstructing an NM image. In some embodiments of theinvention, hot regions outside of the heart may be identified asGanglions. The reconstructed combined image, with indications of theganglions may be used with an image navigation system, such as the Cartosystem by Biosense Webster®, which allows navigation of a catheter inthe heart and overlaying of the catheter location on a previouslyacquired image. Such a system is optionally used to guide an ablationcatheter to parts of the heart (e.g., the atria) adjacent ganglions. Toconfirm the presence of ganglions, high frequency stimulation (HFS)stimulation (or other type of stimulation) may be used. Once confirmed,or possibly without HFS stimulation, which results below suggest may beredundant, ablation at or adjacent an identified ganglion may be carriedout. Optionally, the use of precise navigation allows the use of a lowerpower and/or lower number of ablations. For example, fewer than 20, 10,5 or intermediate numbers of ablations per heart and/or ganglions may beapplied. Optionally, lower power, such as 40 watts (e.g., for RFablation), 30 W, 20 W, 10 W, 5 W or intermediate or smaller power levelsare used. Optionally or alternatively, shorter periods of time are used,for example, 60 seconds, 50 seconds, 30 seconds, 20 seconds, 10 secondsor intermediate number or fewer per ablation.

In a first example, a 60 years old Male having a BMI 22 (176 cm/69 kg)and a medical history of Ventricular arrhythmias, chest discomfort, LowEF (LVEF 35%) and non-ischemic cardiomyopathy, was localized, namelyperformed a CT scan and having a set of cardiac sites, referred toherein as GP1, GP2, and GP3 identified according to the method and/orsystem described above with reference to FIGS. 2-3. GP1, GP2, and GP3are depicted in FIGS. 21A, 21B, and 21C where each one of these figuresincludes, from left to right, a transverse cut image, a coronal cutimage, and sagittal cut image. GP1, GP2, and GP3 are localized also inFIGS. 22A and 22B after estimated locations have been correlated with amap of typical anatomical GP locations in the heart. GP1, GP2, and GP3are localized also in FIG. 22C when overlaid on sympathetic synapsedensity maps. The red dots represent the major GP (relatively largersize) and the red areas on myocardium represent minor GP sites(relatively smaller size).

In a second example, a 47 years old Male having a medical history ofparoxysmal atrial fibrillation catheter ablation for PVI and CVI andnormal LV contraction, LVEF=60%, LDDd=47, and LAD (dimension of lt.atrium)=36 is localized, namely performed a CT scan and having a set ofcardiac sites, referred to herein as GP1, GP2, GP3, and GP4 identifiedaccording to the method and/or systems described above with reference toFIGS. 2-3. GP1, GP2, GP3, and GP4 are depicted in FIGS. 23A23B, 23B, 23Cand 23D where each one of the figures includes, from left to right, atransverse cut image, a coronal cut image, and sagittal cut image. Theimages in FIGS. 23A, 23B, 23C and 23D are images that combine the imagescaptured according the method and/or system described above withreference to FIGS. 2-3 and a respective CT image. The location of thelocalized GP sites was integrated into a Carto system for ablationguidance, for example as shown at FIG. 24. The figure shows the locationof GP sites on a rendered anatomical image. An operator may navigate acatheter for ablation of the GP sites based on the rendered anatomicalimage.

Reference is now made to a set of presentations imaging cardiac GP siteson a 3D simulation of the heart of a patient. The GP site was verifiedby measuring the reaction of the target site, for example having avolume with a diameter of less than 10 millimeters (mm), for instance 5mm, for instance 3 mm, to a HFS at each one of the mapped GP sites wherethe ablation itself is performed by a low power of up to 30 watt (W),for example up to 20 W, for instance 10 W, for instance 5 sessions, andfor instance 3 sessions, for about 20-30 seconds in less than 20applications, for example about 3 repeated applications. In thisprocedure, fragmentation changes and termination of the atrialfibrillation are monitored. FIG. 25 depicts HFS application site (markedwith a circle having a dashed pattern) on a 3D simulation of the heartof a patient. The application site is a non GP site. A negative responseto this appliance is demonstrated in FIG. 26. FIGS. 27A and 27B depictHFS application site (marked with a circle having a dashed pattern) on a3D simulation of the heart of a patient. The application site is theRIPV GP Site. A positive response to this appliance is demonstrated inFIG. 28. FIGS. 29 and 30 depict repeating the HFS application at theRIPV GP Site. The positive response to this repetition is demonstratedin FIG. 31.

FIGS. 32 and 33 depict HFS application site (marked with a circle havinga dashed pattern) on a 3D simulation of the heart of a patient. Theapplication site is the LIPV GP Site. This site was ablated by applyinga five sessions of low power applications (up to 20 W), using a catheteras described above. A positive response to this appliance isdemonstrated in FIG. 34. The outcome of an ablation at the LIPV GP Site,localized in FIGS. 35 and 36, is demonstrated by FIGS. 37 and 38 whichdepict the negative HFS response in a post ablation measurement. Thisresponse is indicative of the success of the ablation process, eventhough the target area was treated with limited power in a limitednumber of ablation sessions. The outcome of an ablation at the RIPV GPSite, localized in FIG. 39, is demonstrated by FIGS. 40 and 41 whichdepict the negative HFS response in a post ablation measurement. Thissite was ablated by applying a three sessions of applying low power (upto 20 W), using a catheter as described above. The RSPV GP Site (markedwith a circle having a dashed pattern) in FIGS. 42 and 43 was alsoablated. This site was ablated by applying a three sessions of applyinglow power (up to 20 W), using a catheter as described above.

In a third example, a 72 years old Male having a medical history ofParoxysmal atrial fibrillation/Hypertension/Dyslipidemia, LV contractionis almost normal, LVEF=66%, LVDd=40 mm, and LAD (dimension of lt.atrium)=42 mm is localized, namely performed a CT scan and having a setof cardiac sites, referred to herein as GP1, GP2, GP3, and GP4identified according to the method and/or system described above withreference to FIGS. 2-3. The imaging was performed prior to ablation.GP1, GP2, GP3, and GP4 are depicted in FIGS. 44A, 44B, 44C and 44D whereeach one of the figures includes, from left to right, a transverse cutimage, a coronal cut image, and sagittal cut image. The images in FIGS.44A, 44B, 44C and 44D are images that combine the images capturedaccording the method and/or system described above with reference toFIGS. 2-3 and a respective CT image. The location of the GP sites wasintegrated into a Carto system for ablation guidance, for example asshown at FIG. 45.

In a fourth example, a 72 years old Male having a medical history ofParoxysmal atrial fibrillation/Hypertension, LV contraction is normal,LVEF=58%, LDDd=37, and LAD (dimension of lt. atrium)=37 is localized,namely performed a CT scan and having a set of cardiac sites, referredto herein as GP1, GP2, and GP3 identified according to the method and/orsystem described above with reference to FIGS. 2-3. The imaging wasperformed prior to an electrophysiology (EP) study, which may help inevaluating the patient's condition, for example, to determine if thepatient is suitable for treatment using the methods and/or systemsdescribed herein. GP1, GP2, and GP3 are depicted in FIGS. 46A, 46B, 46B,and 46C where each one of the figures includes, from left to right, atransverse cut image, a coronal cut image, and sagittal cut image. Theimages in FIGS. 46A, 46B, and 46C are images that combine the imagescaptured according to the method and/or system described above withreference to FIGS. 2-3 and a respective CT image. The location of thelocalized GP site (marked with a circle having a dashed pattern) wasintegrated into a Carto system for ablation guidance, for example asshown at FIG. 47.

In the above experiments, we received, in response to applying a limitednumber of sessions of HFS at the GP sites, 100% positive response.Moreover, we learned that applying the same HFS, even multiple times,for instance more than 50 times, at non GP sites—outside of theidentified GP sites achieves a negative response.

In yet another example, a patient with persistent atrial fibrillation(AF) is treated based on the method and/or system described withreference to FIGS. 2-3. FIG. 16-20 are images generated during thevarious points of the method, in accordance with some embodiments of thepresent invention. The patient underwent 123ImiBG D-SPECT imaging beforecatheter ablation. FIG. 16 illustrates the uptake of mIBG in the leftatrium (LA) before high frequency stimulation (HFS). 5 epicardial GPlocations are identified. FIG. 17 illustrates a saturated stated of theimage of FIG. 16, before HFS. FIG. 18 illustrates locations of positiveHFS before the ablation procedure. The positive HFS confirms theepicardial GP locations. FIG. 19 shows location of the ablations. Theablations were performed at locations that correspond to the GPlocations. FIG. 20 illustrates a negative response to repeated HFS atthe GP ablated sites. The negative response denotes that the GPs havebeen treated. Atrial fibrillation may be controlled and/or prevented.

It should be noted that the above description mostly focuses on alocalization of nervous tissue; however, the above protocols, methods,and systems may be used for a localization of endocrine secretingorgan(s) and/or exocrine secreting organ(s) or other information.

It is expected that during the life of a patent maturing from thisapplication many relevant methods and systems will be developed and thescope of the terms an ablation unit, imaging system and methods, acatheter and a modality is intended to include all such new technologiesa priori.

As used herein the term “about” refers to ±10%.

The terms “comprises”, “comprising”, “includes”, “including”, “having”and their conjugates mean “including but not limited to”. This termencompasses the terms “consisting of” and “consisting essentially of”.

The phrase “consisting essentially of” means that the composition ormethod may include additional ingredients and/or steps, but only if theadditional ingredients and/or steps do not materially alter the basicand novel characteristics of the claimed composition or method.

As used herein, the singular form “a”, “an” and “the” include pluralreferences unless the context clearly dictates otherwise. For example,the term “a compound” or “at least one compound” may include a pluralityof compounds, including mixtures thereof.

The word “exemplary” is used herein to mean “serving as an example,instance or illustration”. Any embodiment described as “exemplary” isnot necessarily to be construed as preferred or advantageous over otherembodiments and/or to exclude the incorporation of features from otherembodiments.

The word “optionally” is used herein to mean “is provided in someembodiments and not provided in other embodiments”. Any particularembodiment of the invention may include a plurality of “optional”features unless such features conflict.

Throughout this application, various embodiments of this invention maybe presented in a range format. It should be understood that thedescription in range format is merely for convenience and brevity andshould not be construed as an inflexible limitation on the scope of theinvention. Accordingly, the description of a range should be consideredto have specifically disclosed all the possible subranges as well asindividual numerical values within that range. For example, descriptionof a range such as from 1 to 6 should be considered to have specificallydisclosed subranges such as from 1 to 3, from 1 to 4, from 1 to 5, from2 to 4, from 2 to 6, from 3 to 6 etc., as well as individual numberswithin that range, for example, 1, 2, 3, 4, 5, and 6. This appliesregardless of the breadth of the range.

Whenever a numerical range is indicated herein, it is meant to includeany cited numeral (fractional or integral) within the indicated range.The phrases “ranging/ranges between” a first indicate number and asecond indicate number and “ranging/ranges from” a first indicate number“to” a second indicate number are used herein interchangeably and aremeant to include the first and second indicated numbers and all thefractional and integral numerals therebetween.

It is appreciated that certain features of the invention, which are, forclarity, described in the context of separate embodiments, may also beprovided in combination in a single embodiment. Conversely, variousfeatures of the invention, which are, for brevity, described in thecontext of a single embodiment, may also be provided separately or inany suitable subcombination or as suitable in any other describedembodiment of the invention. Certain features described in the contextof various embodiments are not to be considered essential features ofthose embodiments, unless the embodiment is inoperative without thoseelements.

Although the invention has been described in conjunction with specificembodiments thereof, it is evident that many alternatives, modificationsand variations will be apparent to those skilled in the art.Accordingly, it is intended to embrace all such alternatives,modifications and variations that fall within the spirit and broad scopeof the appended claims.

All publications, patents and patent applications mentioned in thisspecification are herein incorporated in their entirety by referenceinto the specification, to the same extent as if each individualpublication, patent or patent application was specifically andindividually indicated to be incorporated herein by reference. Inaddition, citation or identification of any reference in thisapplication shall not be construed as an admission that such referenceis available as prior art to the present invention. To the extent thatsection headings are used, they should not be construed as necessarilylimiting.

1. A method of medical image processing for images of body structures,comprising: receiving anatomical data to reconstruct an anatomical imageof a region of a body of a patient, said region comprises a portion ofat least one internal body part, which borders or is spaced apart from atarget tissue; receiving functional data from a functional imagingmodality which images at least a portion of the region of the body ofthe patient; processing said anatomical image to generate at least oneimage mask corresponding to a zone outside of said at least one internalbody part; correlating the at least one image mask with the functionaldata for guiding a reconstruction of a functional image depicting saidtarget tissue; and providing the reconstructed functional image.
 2. Themethod of claim 1, wherein the target tissue is a nerve tissue.
 3. Themethod of claim 1, wherein the anatomical data is obtained from ananatomical imaging modality.
 4. (canceled)
 5. The method of claim 1,wherein the at least one image mask is generated based on templates thatdefine the location of target nerve tissue within and/or in proximal tothe at least one internal body part.
 6. The method of claim 1, furthercomprising adjusting the shape of the image mask based on functionaldata readings from corresponding regions that do not include targetnerve tissue.
 7. (canceled)
 8. The method of claim 1, further comprisingnormalizing the functional data based on measurements denoting activityof the target tissue.
 9. (canceled)
 10. The method of claim 1, whereinthe reconstructed functional image contains regions where the targettissue is located and/or precise coordinates of the target tissue. 11.The method of claim 1, wherein there are two image masks, one for thewall of the body structure and another for the outside of the wall ofthe body structure, the two image masks being different from each other.12-14. (canceled)
 15. The method of claim 1, further comprisingidentifying the target tissue based on at least one predefined rule,which comprises comparing an activity level of a radio-labeled tracer toan average value and/or standard deviation of activity level of theradiolabeled tracer across the organ volume. 16-17. (canceled)
 18. Themethod of claim 1, wherein the image mask is a mapping of a 3D volume ora 2D area, for correlating a volume or an area of the anatomical imageto the corresponding functional image. 19-20. (canceled)
 21. The methodof claim 1, further comprising applying the image mask to a registrationof the anatomical image and the functional image.
 22. The method ofclaim 1, further comprising segmenting the anatomical image intodifferent segments to generate the image masks for detecting differentganglionic plexi (GPs) within the different segments. 23-24. (canceled)25. The method of claim 1, wherein different image masks are generatedto detect different nerve structures of different types and/or atdifferent locations.
 26. The method of claim 1, further comprisingcalculating functional activity within the at least one image maskcorrelated with the functional data, and normalizing the calculatedfunctional activity.
 27. The method of claim 1, further comprisingregistering the reconstructed functional image with a navigation systemfor one or both of treatment and diagnosis. 28-37. (canceled)
 38. Themethod of claim 1, wherein the method is performed before an ablationtreatment of the tissue, to identify the location of the tissue.
 39. Amethod of medical image processing for images of nerve tissue of an ANSof a heart, comprising: receiving anatomical image data to reconstructan anatomical image of heart structures innervated by the ANS; receivingfunctional data from a functional imaging modality which images at leastthe heart structures innervated by the ANS; selecting at least one imagemask by processing the anatomical image data, the at least one imagemask corresponding to dimensions of heart chamber walls containing nervetissues; applying the at least one image mask with the functional datafor reconstructing a functional image depicting ganglionic plexi (GPs);and providing the reconstructed functional image.
 40. (canceled)
 41. Themethod of claim 39, wherein the at least one image mask is oversizedcompared to the heart wall chamber.
 42. The method of claim 39, whereinthe at least one image mask is generated based on preselected anatomicalregions of the heart that contain target nerve tissue that haveintensity activity registered within the functional data.
 43. The methodof claim 39, wherein the at least one image mask is generated based ontemplates that define the location of GPs in proximity to heart chamberwalls.
 44. The method of claim 39, wherein the at least one image maskis generated based on templates that define the location of GPs withinheart chamber walls.
 45. The method of claim 39, wherein the at leastone image mask is generated based on templates that define the locationof GPs that are located more than about 2 mm from the heart chamberwalls.
 46. The method of claim 39, further comprising adjusting theshape of the image mask based on functional data readings fromcorresponding regions of blood chambers and/or vessels that do notinclude GPs.
 47. The method of claim 39, further comprising cancellingfunctional data denoting noise from inside blood filled chambers and/orvessels of the heart based on the anatomical data.
 48. (canceled) 49.The method of claim 39, wherein the anatomical images are obtainedduring a cardiac cycle, wherein different spatiotemporal image masks areselected for at least some images obtained during the cardiac cycle, thedifferent spatiotemporal image masks are synchronized with the cardiaccycle to correspond to the same location of the heart.
 50. The method ofclaim 39, wherein the anatomical image is an average image composed ofthe end diastolic volume image and the end systolic volume image. 51-52.(canceled)
 53. The method of claim 39, wherein a first set of imagemasks is selected to correspond to an epicardium and tissue outside themyocardium, and a second set of image masks is selected to correspond tothe myocardium.
 54. The method of claim 39, further comprisingcalculating functional activity within correlated image masks, andnormalizing the calculated activity to identify the GPs.
 55. The methodof claim 54, wherein the functional activity is calculated for all imagemasks within the volume of the heart.
 56. The method of claim 39,further comprising identifying GPs based on at least one predefine rulecomprising the GP being larger than a predefined size.
 57. The method ofclaim 56, wherein the predefined sizes are different for epicardial GPslocated within an epicardium and myocardial GPs located within amyocardium.
 58. The method of claim 39, further comprising identifyingGPs based on at least one predefined rule comprising calculated activityabove a predefined threshold.
 59. The method of claim 58, wherein: thepredefined threshold is based on a predefined factor times a calculatedstandard deviation of activity within the image mask divided by acalculated average activity within the image mask, and a calculatedadjacent activity surrounding an active region is lower than half of theactivity of the active region.
 60. The method of claim 39, furthercomprising calculating at least one parameter for identified GPs. 61.The method of claim 60, wherein the at least one parameter is selectedfrom one or more of: average size, specific activity, power spectra,normalized power spectra and GP connectivity map, number of GPs perpredefined area.
 62. The method of claim 60, wherein the at least oneparameter is calculated for at least one image of the cardiac cycle. 63.The method of claim 60, further comprising identifying changes in the atleast one parameter over time.
 64. (canceled)
 65. The method of claim39, further comprising registering the identified GPs with a navigationsystem for treatment.
 66. A method of medical image processing forimages of one or more ANS components, the method being carried out by atleast one module programmed to carry out the steps of the method, whichcomprise: receiving anatomical data from an anatomical imaging modalityto reconstruct an anatomical image of a region of a body of a patient,said region comprises a portion of at least one internal body part whichborders or comprises an ANS component; receiving functional data from afunctional imaging modality which imaged at least said portion of theregion of the body of the patient; processing said anatomical image togenerate at least one image mask having dimensions that correspond todimensions of said at least one internal body part; applying the atleast one generated image mask with the functional data forreconstructing of a functional image depicting said ANS component; andidentifying one or more ANS components in the functional image.
 67. Amethod of medical image processing for images of GPs of an ANS of aheart, the method being carried out by at least one module programmed tocarry out the steps of the method, which comprise: receiving anatomicalimage data from an anatomical imaging modality to reconstruct ananatomical image of heart structures innervated by the ANS; receiving afunctional data from a functional imaging modality which images at leastthe heart structures innervated by the ANS; generating at least oneimage mask by processing the anatomical image, the at least one imagemask corresponding to dimensions of heart chamber walls containing GPs;and applying the at least one selected image mask with the functionaldata for locating one or more GPs of an ANS of a heart.
 68. A method ofprocessing images of nerve tissue of an ANS of a heart, the methodcomprising: receiving anatomical image data sufficient to reconstruct ananatomical image of heart structures innervated by the ANS; receivingfunctional data from a functional imaging modality, the functional databeing sufficient to reconstruct at least the heart structures innervatedby the ANS; processing the anatomical image data to generate at leastone image mask corresponding to dimensions of heart chamber wallscontaining nerve tissue; applying the at least one image mask with thefunctional data for reconstructing a functional image depictingganglionic plexi (GPs); and providing the reconstructed functionalimage.